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Repository: zhuge2333/4DRadarSLAM
Branch: main
Commit: dd2ee8c23786
Files: 79
Total size: 508.8 KB
Directory structure:
gitextract_sqtxga8a/
├── CMakeLists.txt
├── LICENSE
├── README.md
├── apps/
│ ├── preprocessing_nodelet.cpp
│ ├── radar_graph_slam_nodelet.cpp
│ └── scan_matching_odometry_nodelet.cpp
├── cmake/
│ └── FindG2O.cmake
├── config/
│ └── params.yaml
├── include/
│ ├── dbscan/
│ │ ├── DBSCAN_kdtree.h
│ │ ├── DBSCAN_precomp.h
│ │ └── DBSCAN_simple.h
│ ├── g2o/
│ │ ├── edge_plane_identity.hpp
│ │ ├── edge_plane_parallel.hpp
│ │ ├── edge_plane_prior.hpp
│ │ ├── edge_se3_gt_utm.hpp
│ │ ├── edge_se3_plane.hpp
│ │ ├── edge_se3_priorquat.hpp
│ │ ├── edge_se3_priorvec.hpp
│ │ ├── edge_se3_priorxy.hpp
│ │ ├── edge_se3_priorxyz.hpp
│ │ ├── edge_se3_priorz.hpp
│ │ ├── edge_se3_se3.hpp
│ │ ├── edge_se3_z.hpp
│ │ └── robust_kernel_io.hpp
│ ├── radar_ego_velocity_estimator.h
│ ├── radar_graph_slam/
│ │ ├── graph_slam.hpp
│ │ ├── information_matrix_calculator.hpp
│ │ ├── keyframe.hpp
│ │ ├── keyframe_updater.hpp
│ │ ├── loop_detector.hpp
│ │ ├── map_cloud_generator.hpp
│ │ ├── nmea_sentence_parser.hpp
│ │ ├── polynomial_interpolation.hpp
│ │ ├── registrations.hpp
│ │ ├── ros_time_hash.hpp
│ │ └── ros_utils.hpp
│ ├── rio_utils/
│ │ ├── data_types.h
│ │ ├── math_helper.h
│ │ ├── radar_point_cloud.h
│ │ ├── ros_helper.h
│ │ ├── simple_profiler.h
│ │ └── strapdown.h
│ ├── scan_context/
│ │ ├── KDTreeVectorOfVectorsAdaptor.h
│ │ ├── Scancontext.h
│ │ ├── nanoflann.hpp
│ │ └── tictoc.h
│ └── utility_radar.h
├── launch/
│ ├── radar_graph_slam.launch
│ ├── rosbag_play_radar_carpark1.launch
│ ├── rosbag_play_radar_carpark3.launch
│ ├── rosbag_play_radar_garden.launch
│ ├── rosbag_play_radar_nanyanglink.launch
│ ├── rosbag_play_radar_ntuloop1.launch
│ ├── rosbag_play_radar_ntuloop2.launch
│ ├── rosbag_play_radar_ntuloop3.launch
│ └── rosbag_play_radar_smoke.launch
├── msg/
│ ├── FloorCoeffs.msg
│ └── ScanMatchingStatus.msg
├── nodelet_plugins.xml
├── package.xml
├── rviz/
│ └── radar_graph_slam.rviz
├── setup.py
├── src/
│ ├── g2o/
│ │ └── robust_kernel_io.cpp
│ ├── gps_traj_align.cpp
│ ├── gt_adjust.cpp
│ ├── radar_ego_velocity_estimator.cpp
│ └── radar_graph_slam/
│ ├── Scancontext.cpp
│ ├── __init__.py
│ ├── bag_player.py
│ ├── ford2bag.py
│ ├── graph_slam.cpp
│ ├── information_matrix_calculator.cpp
│ ├── keyframe.cpp
│ ├── loop_detector.cpp
│ ├── map2odom_publisher.py
│ ├── map_cloud_generator.cpp
│ └── registrations.cpp
└── srv/
├── DumpGraph.srv
└── SaveMap.srv
================================================
FILE CONTENTS
================================================
================================================
FILE: CMakeLists.txt
================================================
# SPDX-License-Identifier: BSD-2-Clause
cmake_minimum_required(VERSION 2.8.3)
project(radar_graph_slam)
# Can we use C++17 in indigo?
add_definitions(-msse -msse2 -msse3 -msse4 -msse4.1 -msse4.2)
# add_definitions("-Wall -g")
set(CMAKE_CXX_FLAGS "-msse -msse2 -msse3 -msse4 -msse4.1 -msse4.2")
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_CURRENT_LIST_DIR}/cmake")
# pcl 1.7 causes a segfault when it is built with debug mode
set(CMAKE_BUILD_TYPE "RELEASE")
find_package(catkin REQUIRED COMPONENTS
roscpp
rospy
pcl_ros
geodesy
nmea_msgs
sensor_msgs
geometry_msgs
message_generation
interactive_markers
ndt_omp
fast_gicp
image_transport
cv_bridge
# rosopencv
)
catkin_python_setup()
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
message(STATUS "version: ${OpenCV_VERSION}")
find_package(PCL REQUIRED)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
message(STATUS "PCL_INCLUDE_DIRS:" ${PCL_INCLUDE_DIRS})
message(STATUS "PCL_LIBRARY_DIRS:" ${PCL_LIBRARY_DIRS})
message(STATUS "PCL_DEFINITIONS:" ${PCL_DEFINITIONS})
find_package(G2O REQUIRED)
include_directories(SYSTEM ${G2O_INCLUDE_DIR} ${G2O_INCLUDE_DIRS})
link_directories(${G2O_LIBRARY_DIRS})
# link_libraries(${G2O_LIBRARIES})
find_package(OpenMP)
if (OPENMP_FOUND)
set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
endif()
find_package(GTSAM REQUIRED QUIET)
link_directories(${GTSAM_LIBRARY_DIRS})
find_library(VGICP_CUDA_FOUND NAMES fast_vgicp_cuda)
message(STATUS "VGICP_CUDA_FOUND:" ${VGICP_CUDA_FOUND})
if(VGICP_CUDA_FOUND)
add_definitions(-DUSE_VGICP_CUDA)
endif()
########################
## message generation ##
########################
add_message_files(FILES
FloorCoeffs.msg
ScanMatchingStatus.msg
)
add_service_files(FILES
SaveMap.srv
DumpGraph.srv
)
generate_messages(DEPENDENCIES std_msgs geometry_msgs)
###################################
## catkin specific configuration ##
###################################
catkin_package(
INCLUDE_DIRS include
LIBRARIES radar_graph_slam_nodelet
# CATKIN_DEPENDS pcl_ros roscpp sensor_msgs
DEPENDS system_lib GTSAM OpenCV
)
###########
## Build ##
###########
include_directories(include)
include_directories(
${PCL_INCLUDE_DIRS}
${catkin_INCLUDE_DIRS}
${GTSAM_INCLUDE_DIR}
"~/sensor_ws/devel/include"
)
# nodelets
add_library(preprocessing_nodelet
apps/preprocessing_nodelet.cpp
src/radar_ego_velocity_estimator.cpp
#src/lib/radar_body_velocity_estimator.cpp
#src/lib/radar_body_velocity_estimator_ros.cpp
)
target_link_libraries(preprocessing_nodelet
${catkin_LIBRARIES}
${PCL_LIBRARIES}
${OpenCV_LIBRARIES}
${Boost_LIBRARIES}
)
add_dependencies(preprocessing_nodelet ${PROJECT_NAME}_gencpp)
add_library(scan_matching_odometry_nodelet
apps/scan_matching_odometry_nodelet.cpp
src/radar_graph_slam/registrations.cpp
)
target_link_libraries(scan_matching_odometry_nodelet
${catkin_LIBRARIES}
${PCL_LIBRARIES}
)
add_dependencies(scan_matching_odometry_nodelet ${PROJECT_NAME}_gencpp)
add_library(radar_graph_slam_nodelet
apps/radar_graph_slam_nodelet.cpp
src/radar_graph_slam/graph_slam.cpp
src/radar_graph_slam/loop_detector.cpp
src/radar_graph_slam/Scancontext.cpp
src/radar_graph_slam/keyframe.cpp
src/radar_graph_slam/map_cloud_generator.cpp
src/radar_graph_slam/registrations.cpp
src/radar_graph_slam/information_matrix_calculator.cpp
src/g2o/robust_kernel_io.cpp
)
target_link_libraries(radar_graph_slam_nodelet
${catkin_LIBRARIES}
${OpenCV_LIBS}
${PCL_LIBRARIES}
${G2O_TYPES_DATA}
${G2O_CORE_LIBRARY}
${G2O_STUFF_LIBRARY}
${G2O_SOLVER_PCG}
${G2O_SOLVER_CSPARSE} # be aware of that CSPARSE is released under LGPL
${G2O_SOLVER_CHOLMOD} # be aware of that cholmod is released under GPL
${G2O_TYPES_SLAM3D}
${G2O_TYPES_SLAM3D_ADDONS}
)
add_dependencies(radar_graph_slam_nodelet ${PROJECT_NAME}_gencpp)
# Adjust Groundtruth
add_executable(gt_adjust src/gt_adjust.cpp )
target_link_libraries(gt_adjust
radar_graph_slam_nodelet
${catkin_LIBRARIES}
${Boost_LIBRARIES}
${G2O_TYPES_DATA}
${G2O_CORE_LIBRARY}
${G2O_STUFF_LIBRARY}
${G2O_SOLVER_PCG}
${G2O_SOLVER_CSPARSE} # be aware of that CSPARSE is released under LGPL
${G2O_SOLVER_CHOLMOD} # be aware of that cholmod is released under GPL
${G2O_TYPES_SLAM3D}
${G2O_TYPES_SLAM3D_ADDONS}
)
# Calculate UTM->world Transform
add_executable(gps_traj_align src/gps_traj_align.cpp )
target_link_libraries(gps_traj_align
radar_graph_slam_nodelet
${catkin_LIBRARIES}
${Boost_LIBRARIES}
${G2O_TYPES_DATA}
${G2O_CORE_LIBRARY}
${G2O_STUFF_LIBRARY}
${G2O_SOLVER_PCG}
${G2O_SOLVER_CSPARSE} # be aware of that CSPARSE is released under LGPL
${G2O_SOLVER_CHOLMOD} # be aware of that cholmod is released under GPL
${G2O_TYPES_SLAM3D}
${G2O_TYPES_SLAM3D_ADDONS}
)
catkin_install_python(
PROGRAMS
src/${PROJECT_NAME}/bag_player.py
src/${PROJECT_NAME}/ford2bag.py
src/${PROJECT_NAME}/map2odom_publisher.py
DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
)
install(FILES nodelet_plugins.xml
DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
)
install(TARGETS
preprocessing_nodelet
scan_matching_odometry_nodelet
radar_graph_slam_nodelet
LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION})
================================================
FILE: LICENSE
================================================
GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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================================================
FILE: README.md
================================================
# 4DRadarSLAM
## A 4D Imaging Radar SLAM System for Large-scale Environments based on Pose Graph Optimization
[Paper (ResearchGate)](https://www.researchgate.net/publication/371309896_4DRadarSLAM_A_4D_Imaging_Radar_SLAM_System_for_Large-scale_Environments_based_on_Pose_Graph_Optimization), [IEEEXplore](https://ieeexplore.ieee.org/document/10160670), [Video](https://www.youtube.com/watch?v=Qlvs7ywA5TI), [Dataset (NTU4DRadLM)](https://github.com/junzhang2016/NTU4DRadLM)
***4DRadarSLAM*** is an open source ROS package for real-time 6DOF SLAM using a 4D Radar. It is based on 3D Graph SLAM with Adaptive Probability Distribution GICP scan matching-based odometry estimation and Intensity Scan Context loop detection. It also supports several graph constraints, such as GPS. We have tested this package with ***Oculli Eagle*** in outdoor structured (buildings), unstructured (trees and grasses) and semi-structured environments.
4DRadarSLAM can operate in adverse wheather. We did a experiment in which sensors are covered by dense ***Smoke***. The Lidar SLAM (R2LIVE) failed, but our 4DRadarSLAM is not affected by it, thanks to the penetration of millimeter waves to small objects such as smoke and rain.
<p align='center'>
<img src="./doc/mapping_smoke.gif" alt="drawing" width="800"/>
</p>
## 1. Dependency
### 1.1 **Ubuntu** and **ROS**
Ubuntu 64-bit 18.04 or 20.04.
ROS Melodic or Noetic. [ROS Installation](http://wiki.ros.org/ROS/Installation):
### 1.2 ***4DRadarSLAM*** requires the following libraries:
- Eigen3
- OpenMP
- PCL
- g2o
### 1.3 The following ROS packages are required:
- geodesy
- nmea_msgs
- pcl_ros
- Our modified [fast_apdgicp](https://github.com/zhuge2333/fast_apdgicp), in which Adaptive Probability Distribution GICP algorithum module is added. The original is [fast_gicp](https://github.com/SMRT-AIST/fast_gicp)
- [barometer_bmp388](https://github.com/zhuge2333/barometer_bmp388.git)
```
sudo apt-get install ros-XXX-geodesy ros-XXX-pcl-ros ros-XXX-nmea-msgs ros-XXX-libg2o
```
**NOTICE:** remember to replace "XXX" on above command as your ROS distributions, for example, if your use ROS-noetic, the command should be:
```
sudo apt-get install ros-noetic-geodesy ros-noetic-pcl-ros ros-noetic-nmea-msgs ros-noetic-libg2o
```
## 2. System architecture
***4DRadarSLAM*** consists of three nodelets.
- *preprocessing_nodelet*
- *scan_matching_odometry_nodelet*
- *radar_graph_slam_nodelet*
The input point cloud is first downsampled by ***preprocessing_nodelet***; the radar pointcloud is transformed to Livox LiDAR frame; estimate its ego velocity and remove dynamic objects, and then passed to the next nodelets. While scan_matching_odometry_nodelet estimates the sensor pose by iteratively applying a scan matching between consecutive frames (i.e., odometry estimation). The estimated odometry are sent to ***radar_graph_slam***. To compensate the accumulated error of the scan matching, it performs loop detection and optimizes a pose graph which takes various constraints into account.
<div align="center">
<img src="doc/fig_flowchart_system.png" width = 100% >
</div>
## 3. Parameter tuning guide
The mapping quality largely depends on the parameter setting. In particular, scan matching parameters have a big impact on the result. Tune the parameters accoding to the following instructions:
### 3.1 Point cloud registration
- ***registration_method***
This parameter allows to change the registration method to be used for odometry estimation and loop detection. Our code gives five options: ICP, NDT_OMP, FAST_GICP, FAST_APDGICP, FAST_VGICP.
FAST_APDGICP is the implementation of our proposed Adaptive Probability Distribution GICP, it utilizes OpenMP for acceleration. Note that FAST_APDGICP requires extra parameters.
Point uncertainty parameters:
- ***dist_var***
- ***azimuth_var***
- ***elevation_var***
*dist_var* means the uncertainty of a point’s range measurement at 100m range, *azimuth_var* and *elevation_var* denote the azimuth and elevation angle accuracy (degree)
### 3.2 Loop detection
- ***accum_distance_thresh***: Minimum distance beteen two edges of the loop
- ***min_loop_interval_dist***: Minimum distance between a new loop edge and the last one
- ***max_baro_difference***: Maximum altitude difference beteen two edges' odometry
- ***max_yaw_difference***: Maximum yaw difference beteen two edges' odometry
- ***odom_check_trans_thresh***: Translation threshold of Odometry Check
- ***odom_check_rot_thresh***: Rotation threshold of Odometry Check
- ***sc_dist_thresh***: Matching score threshold of Scan Context
### 3.3 Other parameters
All the configurable parameters are available in the launch file. Many are similar to the project ***hdl_graph_slam***.
## 4. Run the package
Download [our recorded rosbag](https://drive.google.com/drive/folders/14jVa_dzmckVMDdfELmY32fJlKrZG1Afv?usp=sharing) (**More datasets**: [NTU4DRadLM](https://github.com/junzhang2016/NTU4DRadLM)) and, then
```
roslaunch radar_graph_slam radar_graph_slam.launch
```
You'll see a point cloud like:
<div align="center">
<img src="doc/fig_carpark_map.png" width = 80% >
</div>
You can choose the dataset to play at end of the launch file.
In our paper, we did evaluation on five datasets, mapping results are presented below:
<div align="center">
<img src="doc/fig_map_compare.png" width = 100% >
</div>
## 5. Evaluate the results
In our paper, we use [rpg_trajectory_evaluation](https://github.com/uzh-rpg/rpg_trajectory_evaluation.git), the performance indices used are RE (relative error) and ATE (absolute trajectory error).
## 6. Collect your own datasets
You need a 4D Imaging radar (we use Oculii's Eagle). Also, a barometer (we use BMP388) and GPS/RTK-GPS (we use ZED-F9P) are optional. If you need to compare Lidar SLAM between the algorithum, or use its trajectory as ground truth, calibrating the transform between Radar and Lidar is a precondition.
## 7. Acknowlegement
1. 4DRadarSLAM is based on [koide3/hdl_graph_slam](https://github.com/koide3/hdl_graph_slam)
2. [irapkaist/scancontext](https://github.com/irapkaist/scancontext) scan context
3. [wh200720041/iscloam](https://github.com/wh200720041/iscloam) intensity scan context
4. [christopherdoer/reve](https://github.com/christopherdoer/reve) radar ego-velocity estimator
5. [NeBula-Autonomy/LAMP](https://github.com/NeBula-Autonomy/LAMP) odometry check for loop closure validation
6. [slambook-en](https://github.com/gaoxiang12/slambook-en) and [Dr. Gao Xiang (高翔)](https://github.com/gaoxiang12). His SLAM tutorial and blogs are the starting point of our SLAM journey.
7. [lvt2calib](https://github.com/Clothooo/lvt2calib) by LIUY Clothooo for sensor calibration.
## 8. Citation
If you find this work is useful for your research, please consider citing:
```
@INPROCEEDINGS{ZhangZhuge2023ICRA,
author={Zhang, Jun and Zhuge, Huayang and Wu, Zhenyu and Peng, Guohao and Wen, Mingxing and Liu, Yiyao and Wang, Danwei},
booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},
title={4DRadarSLAM: A 4D Imaging Radar SLAM System for Large-scale Environments based on Pose Graph Optimization},
year={2023},
volume={},
number={},
pages={8333-8340},
doi={10.1109/ICRA48891.2023.10160670}}
```
```
@INPROCEEDINGS{ZhangZhugeLiu2023ITSC,
author={Jun Zhang∗, Huayang Zhuge∗, Yiyao Liu∗, Guohao Peng, Zhenyu Wu, Haoyuan Zhang, Qiyang Lyu, Heshan Li, Chunyang Zhao, Dogan Kircali, Sanat Mharolkar, Xun Yang, Su Yi, Yuanzhe Wang+ and Danwei Wang},
booktitle={2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},
title={NTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping},
year={2023},
volume={},
number={},
pages={},
doi={}}
```
================================================
FILE: apps/preprocessing_nodelet.cpp
================================================
// SPDX-License-Identifier: BSD-2-Clause
#include <string>
#include <fstream>
#include <functional>
#include <ros/ros.h>
#include <ros/time.h>
#include <pcl_ros/transforms.h>
#include <pcl_ros/point_cloud.h>
#include <tf/transform_listener.h>
#include <tf/transform_broadcaster.h>
#include <std_msgs/String.h>
#include <sensor_msgs/Imu.h>
#include <sensor_msgs/PointCloud2.h>
#include <sensor_msgs/PointCloud.h>
#include <geometry_msgs/TwistWithCovarianceStamped.h>
#include <nav_msgs/Odometry.h>
#include <nodelet/nodelet.h>
#include <pluginlib/class_list_macros.h>
#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/filters/passthrough.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/approximate_voxel_grid.h>
#include <pcl/filters/radius_outlier_removal.h>
#include <pcl/filters/statistical_outlier_removal.h>
#include <pcl/filters/fast_bilateral.h>
#include <pcl/filters/filter.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <Eigen/Dense>
#include "radar_ego_velocity_estimator.h"
#include "rio_utils/radar_point_cloud.h"
#include "utility_radar.h"
using namespace std;
namespace radar_graph_slam {
class PreprocessingNodelet : public nodelet::Nodelet, public ParamServer {
public:
// typedef pcl::PointXYZI PointT;
typedef pcl::PointXYZI PointT;
PreprocessingNodelet() {}
virtual ~PreprocessingNodelet() {}
virtual void onInit() {
nh = getNodeHandle();
private_nh = getPrivateNodeHandle();
initializeTransformation();
initializeParams();
points_sub = nh.subscribe(pointCloudTopic, 64, &PreprocessingNodelet::cloud_callback, this);
imu_sub = nh.subscribe(imuTopic, 1, &PreprocessingNodelet::imu_callback, this);
command_sub = nh.subscribe("/command", 10, &PreprocessingNodelet::command_callback, this);
points_pub = nh.advertise<sensor_msgs::PointCloud2>("/filtered_points", 32);
colored_pub = nh.advertise<sensor_msgs::PointCloud2>("/colored_points", 32);
imu_pub = nh.advertise<sensor_msgs::Imu>("/imu", 32);
gt_pub = nh.advertise<nav_msgs::Odometry>("/aftmapped_to_init", 16);
std::string topic_twist = private_nh.param<std::string>("topic_twist", "/eagle_data/twist");
std::string topic_inlier_pc2 = private_nh.param<std::string>("topic_inlier_pc2", "/eagle_data/inlier_pc2");
std::string topic_outlier_pc2 = private_nh.param<std::string>("topic_outlier_pc2", "/eagle_data/outlier_pc2");
pub_twist = nh.advertise<geometry_msgs::TwistWithCovarianceStamped>(topic_twist, 5);
pub_inlier_pc2 = nh.advertise<sensor_msgs::PointCloud2>(topic_inlier_pc2, 5);
pub_outlier_pc2 = nh.advertise<sensor_msgs::PointCloud2>(topic_outlier_pc2, 5);
pc2_raw_pub = nh.advertise<sensor_msgs::PointCloud2>("/eagle_data/pc2_raw",1);
enable_dynamic_object_removal = private_nh.param<bool>("enable_dynamic_object_removal", false);
power_threshold = private_nh.param<float>("power_threshold", 0);
}
private:
void initializeTransformation(){
livox_to_RGB = (cv::Mat_<double>(4,4) <<
-0.006878330000, -0.999969000000, 0.003857230000, 0.029164500000,
-7.737180000000E-05, -0.003856790000, -0.999993000000, 0.045695200000,
0.999976000000, -0.006878580000, -5.084110000000E-05, -0.19018000000,
0, 0, 0, 1);
RGB_to_livox =livox_to_RGB.inv();
Thermal_to_RGB = (cv::Mat_<double>(4,4) <<
0.9999526089706319, 0.008963747151337641, -0.003798822163962599, 0.18106962419014,
-0.008945181135788245, 0.9999481006917174, 0.004876439015823288, -0.04546324090016857,
0.00384233617405678, -0.004842226763999368, 0.999980894463835, 0.08046453079998771,
0,0,0,1);
Radar_to_Thermal = (cv::Mat_<double>(4,4) <<
0.999665, 0.00925436, -0.0241851, -0.0248342,
-0.00826999, 0.999146, 0.0404891, 0.0958317,
0.0245392, -0.0402755, 0.998887, 0.0268037,
0, 0, 0, 1);
Change_Radarframe=(cv::Mat_<double>(4,4) <<
0,-1,0,0,
0,0,-1,0,
1,0,0,0,
0,0,0,1);
Radar_to_livox=RGB_to_livox*Thermal_to_RGB*Radar_to_Thermal*Change_Radarframe;
std::cout << "Radar_to_livox = "<< std::endl << " " << Radar_to_livox << std::endl << std::endl;
}
void initializeParams() {
std::string downsample_method = private_nh.param<std::string>("downsample_method", "VOXELGRID");
double downsample_resolution = private_nh.param<double>("downsample_resolution", 0.1);
if(downsample_method == "VOXELGRID") {
std::cout << "downsample: VOXELGRID " << downsample_resolution << std::endl;
auto voxelgrid = new pcl::VoxelGrid<PointT>();
voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter.reset(voxelgrid);
} else if(downsample_method == "APPROX_VOXELGRID") {
std::cout << "downsample: APPROX_VOXELGRID " << downsample_resolution << std::endl;
pcl::ApproximateVoxelGrid<PointT>::Ptr approx_voxelgrid(new pcl::ApproximateVoxelGrid<PointT>());
approx_voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter = approx_voxelgrid;
} else {
if(downsample_method != "NONE") {
std::cerr << "warning: unknown downsampling type (" << downsample_method << ")" << std::endl;
std::cerr << " : use passthrough filter" << std::endl;
}
std::cout << "downsample: NONE" << std::endl;
}
std::string outlier_removal_method = private_nh.param<std::string>("outlier_removal_method", "STATISTICAL");
if(outlier_removal_method == "STATISTICAL") {
int mean_k = private_nh.param<int>("statistical_mean_k", 20);
double stddev_mul_thresh = private_nh.param<double>("statistical_stddev", 1.0);
std::cout << "outlier_removal: STATISTICAL " << mean_k << " - " << stddev_mul_thresh << std::endl;
pcl::StatisticalOutlierRemoval<PointT>::Ptr sor(new pcl::StatisticalOutlierRemoval<PointT>());
sor->setMeanK(mean_k);
sor->setStddevMulThresh(stddev_mul_thresh);
outlier_removal_filter = sor;
} else if(outlier_removal_method == "RADIUS") {
double radius = private_nh.param<double>("radius_radius", 0.8);
int min_neighbors = private_nh.param<int>("radius_min_neighbors", 2);
std::cout << "outlier_removal: RADIUS " << radius << " - " << min_neighbors << std::endl;
pcl::RadiusOutlierRemoval<PointT>::Ptr rad(new pcl::RadiusOutlierRemoval<PointT>());
rad->setRadiusSearch(radius);
rad->setMinNeighborsInRadius(min_neighbors);
outlier_removal_filter = rad;
}
// else if (outlier_removal_method == "BILATERAL")
// {
// double sigma_s = private_nh.param<double>("bilateral_sigma_s", 5.0);
// double sigma_r = private_nh.param<double>("bilateral_sigma_r", 0.03);
// std::cout << "outlier_removal: BILATERAL " << sigma_s << " - " << sigma_r << std::endl;
// pcl::FastBilateralFilter<PointT>::Ptr fbf(new pcl::FastBilateralFilter<PointT>());
// fbf->setSigmaS (sigma_s);
// fbf->setSigmaR (sigma_r);
// outlier_removal_filter = fbf;
// }
else {
std::cout << "outlier_removal: NONE" << std::endl;
}
use_distance_filter = private_nh.param<bool>("use_distance_filter", true);
distance_near_thresh = private_nh.param<double>("distance_near_thresh", 1.0);
distance_far_thresh = private_nh.param<double>("distance_far_thresh", 100.0);
z_low_thresh = private_nh.param<double>("z_low_thresh", -5.0);
z_high_thresh = private_nh.param<double>("z_high_thresh", 20.0);
std::string file_name = private_nh.param<std::string>("gt_file_location", "");
publish_tf = private_nh.param<bool>("publish_tf", false);
ifstream file_in(file_name);
if (!file_in.is_open()) {
cout << "Can not open this gt file" << endl;
}
else{
std::vector<std::string> vectorLines;
std::string line;
while (getline(file_in, line)) {
vectorLines.push_back(line);
}
for (size_t i = 1; i < vectorLines.size(); i++) {
std::string line_ = vectorLines.at(i);
double stamp,tx,ty,tz,qx,qy,qz,qw;
stringstream data(line_);
data >> stamp >> tx >> ty >> tz >> qx >> qy >> qz >> qw;
nav_msgs::Odometry odom_msg;
odom_msg.header.frame_id = mapFrame;
odom_msg.child_frame_id = baselinkFrame;
odom_msg.header.stamp = ros::Time().fromSec(stamp);
odom_msg.pose.pose.orientation.w = qw;
odom_msg.pose.pose.orientation.x = qx;
odom_msg.pose.pose.orientation.y = qy;
odom_msg.pose.pose.orientation.z = qz;
odom_msg.pose.pose.position.x = tx;
odom_msg.pose.pose.position.y = ty;
odom_msg.pose.pose.position.z = tz;
std::lock_guard<std::mutex> lock(odom_queue_mutex);
odom_msgs.push_back(odom_msg);
}
}
file_in.close();
}
void imu_callback(const sensor_msgs::ImuConstPtr& imu_msg) {
sensor_msgs::Imu imu_data;
imu_data.header.stamp = imu_msg->header.stamp;
imu_data.header.seq = imu_msg->header.seq;
imu_data.header.frame_id = "imu_frame";
Eigen::Quaterniond q_ahrs(imu_msg->orientation.w,
imu_msg->orientation.x,
imu_msg->orientation.y,
imu_msg->orientation.z);
Eigen::Quaterniond q_r =
Eigen::AngleAxisd( M_PI, Eigen::Vector3d::UnitZ()) *
Eigen::AngleAxisd( M_PI, Eigen::Vector3d::UnitY()) *
Eigen::AngleAxisd( 0.00000, Eigen::Vector3d::UnitX());
Eigen::Quaterniond q_rr =
Eigen::AngleAxisd( 0.00000, Eigen::Vector3d::UnitZ()) *
Eigen::AngleAxisd( 0.00000, Eigen::Vector3d::UnitY()) *
Eigen::AngleAxisd( M_PI, Eigen::Vector3d::UnitX());
Eigen::Quaterniond q_out = q_r * q_ahrs * q_rr;
imu_data.orientation.w = q_out.w();
imu_data.orientation.x = q_out.x();
imu_data.orientation.y = q_out.y();
imu_data.orientation.z = q_out.z();
imu_data.angular_velocity.x = imu_msg->angular_velocity.x;
imu_data.angular_velocity.y = -imu_msg->angular_velocity.y;
imu_data.angular_velocity.z = -imu_msg->angular_velocity.z;
imu_data.linear_acceleration.x = imu_msg->linear_acceleration.x;
imu_data.linear_acceleration.y = -imu_msg->linear_acceleration.y;
imu_data.linear_acceleration.z = -imu_msg->linear_acceleration.z;
imu_pub.publish(imu_data);
// imu_queue.push_back(imu_msg);
double time_now = imu_msg->header.stamp.toSec();
bool updated = false;
if (odom_msgs.size() != 0) {
while (odom_msgs.front().header.stamp.toSec() + 0.001 < time_now) {
std::lock_guard<std::mutex> lock(odom_queue_mutex);
odom_msgs.pop_front();
updated = true;
if (odom_msgs.size() == 0)
break;
}
}
if (updated == true && odom_msgs.size() > 0){
if (publish_tf) {
geometry_msgs::TransformStamped tf_msg;
tf_msg.child_frame_id = baselinkFrame;
tf_msg.header.frame_id = mapFrame;
tf_msg.header.stamp = odom_msgs.front().header.stamp;
// tf_msg.header.stamp = ros::Time().now();
tf_msg.transform.rotation = odom_msgs.front().pose.pose.orientation;
tf_msg.transform.translation.x = odom_msgs.front().pose.pose.position.x;
tf_msg.transform.translation.y = odom_msgs.front().pose.pose.position.y;
tf_msg.transform.translation.z = odom_msgs.front().pose.pose.position.z;
tf_broadcaster.sendTransform(tf_msg);
}
gt_pub.publish(odom_msgs.front());
}
}
void cloud_callback(const sensor_msgs::PointCloud::ConstPtr& eagle_msg) { // const pcl::PointCloud<PointT>& src_cloud_r
RadarPointCloudType radarpoint_raw;
PointT radarpoint_xyzi;
pcl::PointCloud<RadarPointCloudType>::Ptr radarcloud_raw( new pcl::PointCloud<RadarPointCloudType> );
pcl::PointCloud<PointT>::Ptr radarcloud_xyzi( new pcl::PointCloud<PointT> );
radarcloud_xyzi->header.frame_id = baselinkFrame;
radarcloud_xyzi->header.seq = eagle_msg->header.seq;
radarcloud_xyzi->header.stamp = eagle_msg->header.stamp.toSec() * 1e6;
for(int i = 0; i < eagle_msg->points.size(); i++)
{
// cout << i << ": " <<eagle_msg->points[i].x<<endl;
if(eagle_msg->channels[2].values[i] > power_threshold) //"Power"
{
if (eagle_msg->points[i].x == NAN || eagle_msg->points[i].y == NAN || eagle_msg->points[i].z == NAN) continue;
if (eagle_msg->points[i].x == INFINITY || eagle_msg->points[i].y == INFINITY || eagle_msg->points[i].z == INFINITY) continue;
cv::Mat ptMat, dstMat;
ptMat = (cv::Mat_<double>(4, 1) << eagle_msg->points[i].x, eagle_msg->points[i].y, eagle_msg->points[i].z, 1);
// Perform matrix multiplication and save as Mat_ for easy element access
dstMat= Radar_to_livox * ptMat;
radarpoint_raw.x = dstMat.at<double>(0,0);
radarpoint_raw.y = dstMat.at<double>(1,0);
radarpoint_raw.z = dstMat.at<double>(2,0);
radarpoint_raw.intensity = eagle_msg->channels[2].values[i];
radarpoint_raw.doppler = eagle_msg->channels[0].values[i];
radarpoint_xyzi.x = dstMat.at<double>(0,0);
radarpoint_xyzi.y = dstMat.at<double>(1,0);
radarpoint_xyzi.z = dstMat.at<double>(2,0);
radarpoint_xyzi.intensity = eagle_msg->channels[2].values[i];
radarcloud_raw->points.push_back(radarpoint_raw);
radarcloud_xyzi->points.push_back(radarpoint_xyzi);
}
}
//********** Publish PointCloud2 Format Raw Cloud **********
sensor_msgs::PointCloud2 pc2_raw_msg;
pcl::toROSMsg(*radarcloud_raw, pc2_raw_msg);
pc2_raw_msg.header.stamp = eagle_msg->header.stamp;
pc2_raw_msg.header.frame_id = baselinkFrame;
pc2_raw_pub.publish(pc2_raw_msg);
//********** Ego Velocity Estimation **********
Eigen::Vector3d v_r, sigma_v_r;
sensor_msgs::PointCloud2 inlier_radar_msg, outlier_radar_msg;
clock_t start_ms = clock();
if (estimator.estimate(pc2_raw_msg, v_r, sigma_v_r, inlier_radar_msg, outlier_radar_msg))
{
clock_t end_ms = clock();
double time_used = double(end_ms - start_ms) / CLOCKS_PER_SEC;
egovel_time.push_back(time_used);
geometry_msgs::TwistWithCovarianceStamped twist;
twist.header.stamp = pc2_raw_msg.header.stamp;
twist.twist.twist.linear.x = v_r.x();
twist.twist.twist.linear.y = v_r.y();
twist.twist.twist.linear.z = v_r.z();
twist.twist.covariance.at(0) = std::pow(sigma_v_r.x(), 2);
twist.twist.covariance.at(7) = std::pow(sigma_v_r.y(), 2);
twist.twist.covariance.at(14) = std::pow(sigma_v_r.z(), 2);
pub_twist.publish(twist);
pub_inlier_pc2.publish(inlier_radar_msg);
pub_outlier_pc2.publish(outlier_radar_msg);
}
else{;}
pcl::PointCloud<PointT>::Ptr radarcloud_inlier( new pcl::PointCloud<PointT> );
pcl::fromROSMsg (inlier_radar_msg, *radarcloud_inlier);
pcl::PointCloud<PointT>::ConstPtr src_cloud;
if (enable_dynamic_object_removal)
src_cloud = radarcloud_inlier;
else
src_cloud = radarcloud_xyzi;
if(src_cloud->empty()) {
return;
}
src_cloud = deskewing(src_cloud);
// if baselinkFrame is defined, transform the input cloud to the frame
if(!baselinkFrame.empty()) {
if(!tf_listener.canTransform(baselinkFrame, src_cloud->header.frame_id, ros::Time(0))) {
std::cerr << "failed to find transform between " << baselinkFrame << " and " << src_cloud->header.frame_id << std::endl;
}
tf::StampedTransform transform;
tf_listener.waitForTransform(baselinkFrame, src_cloud->header.frame_id, ros::Time(0), ros::Duration(2.0));
tf_listener.lookupTransform(baselinkFrame, src_cloud->header.frame_id, ros::Time(0), transform);
pcl::PointCloud<PointT>::Ptr transformed(new pcl::PointCloud<PointT>());
pcl_ros::transformPointCloud(*src_cloud, *transformed, transform);
transformed->header.frame_id = baselinkFrame;
transformed->header.stamp = src_cloud->header.stamp;
src_cloud = transformed;
}
pcl::PointCloud<PointT>::ConstPtr filtered = distance_filter(src_cloud);
// filtered = passthrough(filtered);
filtered = downsample(filtered);
filtered = outlier_removal(filtered);
// Distance Histogram
static size_t num_frame = 0;
if (num_frame % 10 == 0) {
Eigen::VectorXi num_at_dist = Eigen::VectorXi::Zero(100);
for (int i = 0; i < filtered->size(); i++){
int dist = floor(filtered->at(i).getVector3fMap().norm());
if (dist < 100)
num_at_dist(dist) += 1;
}
num_at_dist_vec.push_back(num_at_dist);
}
points_pub.publish(*filtered);
}
pcl::PointCloud<PointT>::ConstPtr passthrough(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
PointT pt;
for(int i = 0; i < cloud->size(); i++){
if (cloud->at(i).z < 10 && cloud->at(i).z > -2){
pt.x = (*cloud)[i].x;
pt.y = (*cloud)[i].y;
pt.z = (*cloud)[i].z;
pt.intensity = (*cloud)[i].intensity;
filtered->points.push_back(pt);
}
}
filtered->header = cloud->header;
return filtered;
}
pcl::PointCloud<PointT>::ConstPtr downsample(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
if(!downsample_filter) {
// Remove NaN/Inf points
pcl::PointCloud<PointT>::Ptr cloudout(new pcl::PointCloud<PointT>());
std::vector<int> indices;
pcl::removeNaNFromPointCloud(*cloud, *cloudout, indices);
return cloudout;
}
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
downsample_filter->setInputCloud(cloud);
downsample_filter->filter(*filtered);
filtered->header = cloud->header;
return filtered;
}
pcl::PointCloud<PointT>::ConstPtr outlier_removal(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
if(!outlier_removal_filter) {
return cloud;
}
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
outlier_removal_filter->setInputCloud(cloud);
outlier_removal_filter->filter(*filtered);
filtered->header = cloud->header;
return filtered;
}
pcl::PointCloud<PointT>::ConstPtr distance_filter(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
filtered->reserve(cloud->size());
std::copy_if(cloud->begin(), cloud->end(), std::back_inserter(filtered->points), [&](const PointT& p) {
double d = p.getVector3fMap().norm();
double z = p.z;
return d > distance_near_thresh && d < distance_far_thresh && z < z_high_thresh && z > z_low_thresh;
});
// for (size_t i=0; i<cloud->size(); i++){
// const PointT p = cloud->points.at(i);
// double d = p.getVector3fMap().norm();
// double z = p.z;
// if (d > distance_near_thresh && d < distance_far_thresh && z < z_high_thresh && z > z_low_thresh)
// filtered->points.push_back(p);
// }
filtered->width = filtered->size();
filtered->height = 1;
filtered->is_dense = false;
filtered->header = cloud->header;
return filtered;
}
pcl::PointCloud<PointT>::ConstPtr deskewing(const pcl::PointCloud<PointT>::ConstPtr& cloud) {
ros::Time stamp = pcl_conversions::fromPCL(cloud->header.stamp);
if(imu_queue.empty()) {
return cloud;
}
// the color encodes the point number in the point sequence
if(colored_pub.getNumSubscribers()) {
pcl::PointCloud<pcl::PointXYZRGB>::Ptr colored(new pcl::PointCloud<pcl::PointXYZRGB>());
colored->header = cloud->header;
colored->is_dense = cloud->is_dense;
colored->width = cloud->width;
colored->height = cloud->height;
colored->resize(cloud->size());
for(int i = 0; i < cloud->size(); i++) {
double t = static_cast<double>(i) / cloud->size();
colored->at(i).getVector4fMap() = cloud->at(i).getVector4fMap();
colored->at(i).r = 255 * t;
colored->at(i).g = 128;
colored->at(i).b = 255 * (1 - t);
}
colored_pub.publish(*colored);
}
sensor_msgs::ImuConstPtr imu_msg = imu_queue.front();
auto loc = imu_queue.begin();
for(; loc != imu_queue.end(); loc++) {
imu_msg = (*loc);
if((*loc)->header.stamp > stamp) {
break;
}
}
imu_queue.erase(imu_queue.begin(), loc);
Eigen::Vector3f ang_v(imu_msg->angular_velocity.x, imu_msg->angular_velocity.y, imu_msg->angular_velocity.z);
ang_v *= -1;
pcl::PointCloud<PointT>::Ptr deskewed(new pcl::PointCloud<PointT>());
deskewed->header = cloud->header;
deskewed->is_dense = cloud->is_dense;
deskewed->width = cloud->width;
deskewed->height = cloud->height;
deskewed->resize(cloud->size());
double scan_period = private_nh.param<double>("scan_period", 0.1);
for(int i = 0; i < cloud->size(); i++) {
const auto& pt = cloud->at(i);
// TODO: transform IMU data into the LIDAR frame
double delta_t = scan_period * static_cast<double>(i) / cloud->size();
Eigen::Quaternionf delta_q(1, delta_t / 2.0 * ang_v[0], delta_t / 2.0 * ang_v[1], delta_t / 2.0 * ang_v[2]);
Eigen::Vector3f pt_ = delta_q.inverse() * pt.getVector3fMap();
deskewed->at(i) = cloud->at(i);
deskewed->at(i).getVector3fMap() = pt_;
}
return deskewed;
}
bool RadarRaw2PointCloudXYZ(const pcl::PointCloud<RadarPointCloudType>::ConstPtr &raw, pcl::PointCloud<pcl::PointXYZ>::Ptr &cloudxyz)
{
pcl::PointXYZ point_xyz;
for(int i = 0; i < raw->size(); i++)
{
point_xyz.x = (*raw)[i].x;
point_xyz.y = (*raw)[i].y;
point_xyz.z = (*raw)[i].z;
cloudxyz->points.push_back(point_xyz);
}
return true;
}
bool RadarRaw2PointCloudXYZI(const pcl::PointCloud<RadarPointCloudType>::ConstPtr &raw, pcl::PointCloud<pcl::PointXYZI>::Ptr &cloudxyzi)
{
pcl::PointXYZI radarpoint_xyzi;
for(int i = 0; i < raw->size(); i++)
{
radarpoint_xyzi.x = (*raw)[i].x;
radarpoint_xyzi.y = (*raw)[i].y;
radarpoint_xyzi.z = (*raw)[i].z;
radarpoint_xyzi.intensity = (*raw)[i].intensity;
cloudxyzi->points.push_back(radarpoint_xyzi);
}
return true;
}
void command_callback(const std_msgs::String& str_msg) {
if (str_msg.data == "time") {
std::sort(egovel_time.begin(), egovel_time.end());
double median = egovel_time.at(size_t(egovel_time.size() / 2));
cout << "Ego velocity time cost (median): " << median << endl;
}
else if (str_msg.data == "point_distribution") {
Eigen::VectorXi data(100);
for (size_t i = 0; i < num_at_dist_vec.size(); i++){ // N
Eigen::VectorXi& nad = num_at_dist_vec.at(i);
for (int j = 0; j< 100; j++){
data(j) += nad(j);
}
}
data /= num_at_dist_vec.size();
for (int i=0; i<data.size(); i++){
cout << data(i) << ", ";
}
cout << endl;
}
}
private:
ros::NodeHandle nh;
ros::NodeHandle private_nh;
ros::Subscriber imu_sub;
std::vector<sensor_msgs::ImuConstPtr> imu_queue;
ros::Subscriber points_sub;
ros::Publisher points_pub;
ros::Publisher colored_pub;
ros::Publisher imu_pub;
ros::Publisher gt_pub;
tf::TransformListener tf_listener;
tf::TransformBroadcaster tf_broadcaster;
bool use_distance_filter;
double distance_near_thresh;
double distance_far_thresh;
double z_low_thresh;
double z_high_thresh;
pcl::Filter<PointT>::Ptr downsample_filter;
pcl::Filter<PointT>::Ptr outlier_removal_filter;
cv::Mat Radar_to_livox; // Transform Radar point cloud to LiDAR Frame
cv::Mat Thermal_to_RGB,Radar_to_Thermal,RGB_to_livox,livox_to_RGB,Change_Radarframe;
rio::RadarEgoVelocityEstimator estimator;
ros::Publisher pub_twist, pub_inlier_pc2, pub_outlier_pc2, pc2_raw_pub;
float power_threshold;
bool enable_dynamic_object_removal = false;
std::mutex odom_queue_mutex;
std::deque<nav_msgs::Odometry> odom_msgs;
bool publish_tf;
ros::Subscriber command_sub;
std::vector<double> egovel_time;
std::vector<Eigen::VectorXi> num_at_dist_vec;
};
} // namespace radar_graph_slam
PLUGINLIB_EXPORT_CLASS(radar_graph_slam::PreprocessingNodelet, nodelet::Nodelet)
================================================
FILE: apps/radar_graph_slam_nodelet.cpp
================================================
// SPDX-License-Identifier: BSD-2-Clause
#include <ctime>
#include <mutex>
#include <atomic>
#include <memory>
#include <iomanip>
#include <iostream>
#include <fstream>
#include <string>
#include <unordered_map>
#include <boost/format.hpp>
#include <boost/thread.hpp>
#include <boost/filesystem.hpp>
#include <boost/algorithm/string.hpp>
#include <Eigen/Dense>
#include <pcl/io/pcd_io.h>
#include <pcl_ros/point_cloud.h>
#include <pcl/registration/icp.h>
#include <pcl/octree/octree_search.h>
#include <ros/ros.h>
#include <geodesy/utm.h>
#include <geodesy/wgs84.h>
#include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h>
#include <message_filters/sync_policies/approximate_time.h>
#include <tf_conversions/tf_eigen.h>
#include <tf/transform_listener.h>
#include <tf/transform_broadcaster.h>
#include <std_msgs/Time.h>
#include <std_msgs/String.h>
#include <nav_msgs/Odometry.h>
#include <nmea_msgs/Sentence.h>
#include <sensor_msgs/Imu.h>
#include <sensor_msgs/NavSatFix.h>
#include <sensor_msgs/PointCloud2.h>
#include <geographic_msgs/GeoPointStamped.h>
#include <visualization_msgs/MarkerArray.h>
#include <nodelet/nodelet.h>
#include <pluginlib/class_list_macros.h>
#include <radar_graph_slam/SaveMap.h>
#include <radar_graph_slam/DumpGraph.h>
#include <radar_graph_slam/ros_utils.hpp>
#include <radar_graph_slam/ros_time_hash.hpp>
#include <radar_graph_slam/FloorCoeffs.h>
#include <radar_graph_slam/graph_slam.hpp>
#include <radar_graph_slam/keyframe.hpp>
#include <radar_graph_slam/keyframe_updater.hpp>
#include <radar_graph_slam/loop_detector.hpp>
#include <radar_graph_slam/information_matrix_calculator.hpp>
#include <radar_graph_slam/map_cloud_generator.hpp>
#include <radar_graph_slam/nmea_sentence_parser.hpp>
#include "radar_graph_slam/polynomial_interpolation.hpp"
#include <radar_graph_slam/registrations.hpp>
#include "scan_context/Scancontext.h"
#include <g2o/types/slam3d/edge_se3.h>
#include <g2o/types/slam3d/vertex_se3.h>
#include <g2o/edge_se3_plane.hpp>
#include <g2o/edge_se3_priorxy.hpp>
#include <g2o/edge_se3_priorxyz.hpp>
#include <g2o/edge_se3_priorz.hpp>
#include <g2o/edge_se3_priorvec.hpp>
#include <g2o/edge_se3_priorquat.hpp>
#include <barometer_bmp388/Barometer.h>
#include "utility_radar.h"
using namespace std;
namespace radar_graph_slam {
class RadarGraphSlamNodelet : public nodelet::Nodelet, public ParamServer {
public:
typedef pcl::PointXYZI PointT;
typedef PointXYZIRPYT PointTypePose;
typedef message_filters::sync_policies::ApproximateTime<nav_msgs::Odometry, sensor_msgs::PointCloud2> ApproxSyncPolicy;
RadarGraphSlamNodelet() {}
virtual ~RadarGraphSlamNodelet() {}
virtual void onInit() {
nh = getNodeHandle();
mt_nh = getMTNodeHandle();
private_nh = getPrivateNodeHandle();
// init parameters
map_cloud_resolution = private_nh.param<double>("map_cloud_resolution", 0.05);
trans_odom2map.setIdentity();
trans_aftmapped.setIdentity();
trans_aftmapped_incremental.setIdentity();
initial_pose.setIdentity();
max_keyframes_per_update = private_nh.param<int>("max_keyframes_per_update", 10);
anchor_node = nullptr;
anchor_edge = nullptr;
floor_plane_node = nullptr;
graph_slam.reset(new GraphSLAM(private_nh.param<std::string>("g2o_solver_type", "lm_var")));
keyframe_updater.reset(new KeyframeUpdater(private_nh));
loop_detector.reset(new LoopDetector(private_nh));
map_cloud_generator.reset(new MapCloudGenerator());
inf_calclator.reset(new InformationMatrixCalculator(private_nh));
nmea_parser.reset(new NmeaSentenceParser());
gps_edge_intervals = private_nh.param<int>("gps_edge_intervals", 10);
gps_time_offset = private_nh.param<double>("gps_time_offset", 0.0);
gps_edge_stddev_xy = private_nh.param<double>("gps_edge_stddev_xy", 10000.0);
gps_edge_stddev_z = private_nh.param<double>("gps_edge_stddev_z", 10.0);
max_gps_edge_stddev_xy = private_nh.param<double>("max_gps_edge_stddev_xy", 1.0);
max_gps_edge_stddev_z = private_nh.param<double>("max_gps_edge_stddev_z", 2.0);
// Preintegration Parameters
enable_preintegration = private_nh.param<bool>("enable_preintegration", false);
use_egovel_preinteg_trans = private_nh.param<bool>("use_egovel_preinteg_trans", false);
preinteg_trans_stddev = private_nh.param<double>("preinteg_trans_stddev", 1.0);
preinteg_orient_stddev = private_nh.param<double>("preinteg_orient_stddev", 2.0);
enable_barometer = private_nh.param<bool>("enable_barometer", false);
barometer_edge_type = private_nh.param<int>("barometer_edge_type", 2);
barometer_edge_stddev = private_nh.param<double>("barometer_edge_stddev", 0.5);
points_topic = private_nh.param<std::string>("points_topic", "/radar_enhanced_pcl");
show_sphere = private_nh.param<bool>("show_sphere", false);
dataset_name = private_nh.param<std::string>("dataset_name", "");
registration = select_registration_method(private_nh);
// subscribers
odom_sub.reset(new message_filters::Subscriber<nav_msgs::Odometry>(mt_nh, odomTopic, 256));
cloud_sub.reset(new message_filters::Subscriber<sensor_msgs::PointCloud2>(mt_nh, "/filtered_points", 32));
sync.reset(new message_filters::Synchronizer<ApproxSyncPolicy>(ApproxSyncPolicy(32), *odom_sub, *cloud_sub));
sync->registerCallback(boost::bind(&RadarGraphSlamNodelet::cloud_callback, this, _1, _2));
if(private_nh.param<bool>("enable_gps", true)) {
gps_sub = mt_nh.subscribe("/gps/geopoint", 1024, &RadarGraphSlamNodelet::gps_callback, this);
nmea_sub = mt_nh.subscribe("/gpsimu_driver/nmea_sentence", 1024, &RadarGraphSlamNodelet::nmea_callback, this);
navsat_sub = mt_nh.subscribe(gpsTopic, 1024, &RadarGraphSlamNodelet::navsat_callback, this);
}
if(private_nh.param<bool>("enable_barometer", false)) {
barometer_sub = mt_nh.subscribe("/barometer/filtered", 16, &RadarGraphSlamNodelet::barometer_callback, this);
}
if (enable_preintegration)
imu_odom_sub = nh.subscribe("/imu_pre_integ/imu_odom_incre", 1024, &RadarGraphSlamNodelet::imu_odom_callback, this);
imu_sub = nh.subscribe("/imu", 1024, &RadarGraphSlamNodelet::imu_callback, this);
command_sub = nh.subscribe("/command", 10, &RadarGraphSlamNodelet::command_callback, this);
//***** publishers ******
markers_pub = mt_nh.advertise<visualization_msgs::MarkerArray>("/radar_graph_slam/markers", 16);
// Transform RadarOdom_to_base
odom2base_pub = mt_nh.advertise<geometry_msgs::TransformStamped>("/radar_graph_slam/odom2base", 16);
aftmapped_odom_pub = mt_nh.advertise<nav_msgs::Odometry>("/radar_graph_slam/aftmapped_odom", 16);
aftmapped_odom_incremenral_pub = mt_nh.advertise<nav_msgs::Odometry>("/radar_graph_slam/aftmapped_odom_incremental", 16);
map_points_pub = mt_nh.advertise<sensor_msgs::PointCloud2>("/radar_graph_slam/map_points", 1, true);
read_until_pub = mt_nh.advertise<std_msgs::Header>("/radar_graph_slam/read_until", 32);
odom_frame2frame_pub = mt_nh.advertise<nav_msgs::Odometry>("/radar_graph_slam/odom_frame2frame", 16);
dump_service_server = mt_nh.advertiseService("/radar_graph_slam/dump", &RadarGraphSlamNodelet::dump_service, this);
save_map_service_server = mt_nh.advertiseService("/radar_graph_slam/save_map", &RadarGraphSlamNodelet::save_map_service, this);
graph_updated = false;
double graph_update_interval = private_nh.param<double>("graph_update_interval", 3.0);
double map_cloud_update_interval = private_nh.param<double>("map_cloud_update_interval", 10.0);
optimization_timer = mt_nh.createWallTimer(ros::WallDuration(graph_update_interval), &RadarGraphSlamNodelet::optimization_timer_callback, this);
map_publish_timer = mt_nh.createWallTimer(ros::WallDuration(map_cloud_update_interval), &RadarGraphSlamNodelet::map_points_publish_timer_callback, this);
if (dataset_name == "loop3")
utm_to_world <<
-0.057621, 0.996222, -0.064972, -128453.624105,
-0.998281, -0.058194, -0.006954, 361869.958099,
-0.010708, 0.064459, 0.997863, -5882.237973,
0.000000, 0.000000, 0.000000, 1.000000;
else if (dataset_name == "loop2")
utm_to_world <<
-0.085585, 0.995774, -0.033303, -117561.214476,
-0.996323, -0.085401, 0.006904, 364927.287181,
0.004031, 0.033772, 0.999421, -6478.377842,
0.000000, 0.000000, 0.000000, 1.000000;
}
private:
/**
* @brief received point clouds are pushed to #keyframe_queue
* @param odom_msg
* @param cloud_msg
*/
void cloud_callback(const nav_msgs::OdometryConstPtr& odom_msg, const sensor_msgs::PointCloud2::ConstPtr& cloud_msg) {
const ros::Time& stamp = cloud_msg->header.stamp;
Eigen::Isometry3d odom_now = odom2isometry(odom_msg);
Eigen::Matrix4d matrix_map2base;
// Publish TF between /map and /base_link
if(keyframes.size() > 0)
{
const KeyFrame::Ptr& keyframe_last = keyframes.back();
Eigen::Isometry3d lastkeyframe_odom_incre = keyframe_last->odom_scan2scan.inverse() * odom_now;
Eigen::Isometry3d keyframe_map2base_matrix = keyframe_last->node->estimate();
// map2base = odom^(-1) * base
matrix_map2base = (keyframe_map2base_matrix * lastkeyframe_odom_incre).matrix();
}
geometry_msgs::TransformStamped map2base_trans = matrix2transform(cloud_msg->header.stamp, matrix_map2base, mapFrame, baselinkFrame);
if (pow(map2base_trans.transform.rotation.w,2)+pow(map2base_trans.transform.rotation.x,2)+
pow(map2base_trans.transform.rotation.y,2)+pow(map2base_trans.transform.rotation.z,2) < pow(0.9,2))
{map2base_trans.transform.rotation.w=1; map2base_trans.transform.rotation.x=0; map2base_trans.transform.rotation.y=0; map2base_trans.transform.rotation.z=0;}
map2base_broadcaster.sendTransform(map2base_trans);
pcl::PointCloud<PointT>::Ptr cloud(new pcl::PointCloud<PointT>());
pcl::fromROSMsg(*cloud_msg, *cloud);
if(baselinkFrame.empty()) {
baselinkFrame = cloud_msg->header.frame_id;
}
// Push ego velocity to queue
geometry_msgs::TwistStamped::Ptr twist_(new geometry_msgs::TwistStamped);
twist_->header.stamp = cloud_msg->header.stamp;
twist_->twist.linear = odom_msg->twist.twist.linear;
{
std::lock_guard<std::mutex> lock(keyframe_queue_mutex);
twist_queue.push_back(twist_);
}
//********** Decided whether to accept the frame as a key frame or not **********
if(!keyframe_updater->decide(odom_now, stamp)) {
std::lock_guard<std::mutex> lock(keyframe_queue_mutex);
if(keyframe_queue.empty()) {
std_msgs::Header read_until;
read_until.stamp = stamp + ros::Duration(10, 0);
read_until.frame_id = points_topic;
read_until_pub.publish(read_until);
read_until.frame_id = "/filtered_points";
read_until_pub.publish(read_until);
}
return;
}
// Get time of this key frame for Intergeration, to integerate between two key frames
thisKeyframeTime = cloud_msg->header.stamp.toSec();
double accum_d = keyframe_updater->get_accum_distance();
// Construct keyframe
KeyFrame::Ptr keyframe(new KeyFrame(keyframe_index, stamp, odom_now, accum_d, cloud));
keyframe_index ++;
if (enable_preintegration){
// Intergerate translation of ego velocity, add rotation
geometry_msgs::Transform transf_integ = preIntegrationTransform();
static uint32_t sequ = 0;
nav_msgs::Odometry odom_frame2frame;
odom_frame2frame.pose.pose.orientation = transf_integ.rotation;
odom_frame2frame.pose.pose.position.x = transf_integ.translation.x;
odom_frame2frame.pose.pose.position.y = transf_integ.translation.y;
odom_frame2frame.pose.pose.position.z = transf_integ.translation.z;
odom_frame2frame.header.frame_id = "map";
odom_frame2frame.header.stamp = cloud_msg->header.stamp;
odom_frame2frame.header.seq = sequ; sequ ++;
odom_frame2frame_pub.publish(odom_frame2frame);
keyframe->trans_integrated = transf_integ;
}
std::lock_guard<std::mutex> lock(keyframe_queue_mutex);
keyframe_queue.push_back(keyframe);
// Scan Context loop detector - giseop
// - SINGLE_SCAN_FULL: using downsampled original point cloud (/full_cloud_projected + downsampling)
// - SINGLE_SCAN_FEAT: using surface feature as an input point cloud for scan context (2020.04.01: checked it works.)
// - MULTI_SCAN_FEAT: using NearKeyframes (because a MulRan scan does not have beyond region, so to solve this issue ... )
const SCInputType sc_input_type = SCInputType::SINGLE_SCAN_FULL; // change this
if( sc_input_type == SCInputType::SINGLE_SCAN_FULL ) {
loop_detector->scManager->makeAndSaveScancontextAndKeys(*cloud);
}
// else if (sc_input_type == SCInputType::SINGLE_SCAN_FEAT) {
// scManager.makeAndSaveScancontextAndKeys(*thisSurfKeyFrame);
// }
// else if (sc_input_type == SCInputType::MULTI_SCAN_FEAT) {
// pcl::PointCloud<PointT>::Ptr multiKeyFrameFeatureCloud(new pcl::PointCloud<PointT>());
// loopFindNearKeyframes(multiKeyFrameFeatureCloud, cloudKeyPoses6D->size() - 1, historyKeyframeSearchNum);
// scManager.makeAndSaveScancontextAndKeys(*multiKeyFrameFeatureCloud);
// }
lastKeyframeTime = thisKeyframeTime;
}
void imu_callback(const sensor_msgs::ImuConstPtr& imu_odom_msg) {
// Transform to Radar's Frame
geometry_msgs::QuaternionStamped::Ptr imu_quat(new geometry_msgs::QuaternionStamped);
imu_quat->quaternion = imu_odom_msg->orientation;
Eigen::Quaterniond imu_quat_from(imu_quat->quaternion.w, imu_quat->quaternion.x, imu_quat->quaternion.y, imu_quat->quaternion.z);
Eigen::Quaterniond imu_quat_deskew = imu_quat_from * extQRPY;
imu_quat_deskew.normalize();
static int cnt = 0;
if(cnt == 0) {
double roll, pitch, yaw;
tf::Quaternion orientation = tf::Quaternion(imu_quat_deskew.x(),imu_quat_deskew.y(),imu_quat_deskew.z(),imu_quat_deskew.w());
tf::quaternionMsgToTF(imu_odom_msg->orientation, orientation);
tf::Matrix3x3(orientation).getRPY(roll, pitch, yaw);
// Eigen::Matrix3d imu_mat_deskew = imu_quat_deskew.toRotationMatrix();
// Eigen::Vector3d eulerAngle = imu_mat_deskew.eulerAngles(0,1,2); // roll pitch yaw
Eigen::AngleAxisd rollAngle(AngleAxisd(roll,Vector3d::UnitX()));
Eigen::AngleAxisd pitchAngle(AngleAxisd(pitch,Vector3d::UnitY()));
Eigen::AngleAxisd yawAngle(AngleAxisd(0.0,Vector3d::UnitZ()));
Eigen::Matrix3d imu_mat_final; imu_mat_final = yawAngle * pitchAngle * rollAngle;
Eigen::Isometry3d isom_initial_pose;
isom_initial_pose.setIdentity();
isom_initial_pose.rotate(imu_mat_final); // Set rotation
initial_pose = isom_initial_pose.matrix();
ROS_INFO("Initial Position Matrix = ");
std::cout <<
initial_pose(0,0) << ", " << initial_pose(0,1) << ", " << initial_pose(0,2) << ", " << initial_pose(0,3) << ", " << std::endl <<
initial_pose(1,0) << ", " << initial_pose(1,1) << ", " << initial_pose(1,2) << ", " << initial_pose(1,3) << ", " << std::endl <<
initial_pose(2,0) << ", " << initial_pose(2,1) << ", " << initial_pose(2,2) << ", " << initial_pose(2,3) << ", " << std::endl <<
initial_pose(3,0) << ", " << initial_pose(3,1) << ", " << initial_pose(3,2) << ", " << initial_pose(3,3) << ", " << std::endl << std::endl;
cnt = 1;
}
}
void imu_odom_callback(const nav_msgs::OdometryConstPtr& imu_odom_msg) {
{
std::lock_guard<std::mutex> lock(keyframe_queue_mutex);
imu_odom_queue.push_back(imu_odom_msg);
}
}
geometry_msgs::Transform preIntegrationTransform(){
double lastImuOdomQT = -1;
// double lastTwistQT = -1;
double delta_t = 0;
size_t imu_odom_end_index = 0; // The index of the last used IMU odom
geometry_msgs::Transform trans_; // Transform to return
// pop old IMU orientation message
while (!imu_odom_queue.empty() && imu_odom_queue.front()->header.stamp.toSec() < lastKeyframeTime - delta_t){
lastImuOdomQT = imu_odom_queue.front()->header.stamp.toSec();
imu_odom_queue.pop_front();
}
// pop old Twist message
while (!twist_queue.empty() && twist_queue.front()->header.stamp.toSec() < lastKeyframeTime - delta_t){
// lastTwistQT = twist_queue.front()->header.stamp.toSec();
twist_queue.pop_front();
}
// repropogate
Eigen::Isometry3d isom_frame2frame; // Translation increment between last key frame and this IMU msg
Eigen::Isometry3d isometry_rotation; // Rotation of IMU odom
Eigen::Isometry3d isometry_translation; // Translation of IMU odom
isom_frame2frame.setIdentity();
isometry_rotation.setIdentity();
geometry_msgs::Vector3 translation_frame2frame; // Translation between two key frames
if (!imu_odom_queue.empty())
{
// (Doing this because some imu_odom later than thisKeyframeTime will be recieved)
for (size_t i = 0; i < imu_odom_queue.size(); ++i){
if (imu_odom_queue.at(i)->header.stamp.toSec() < thisKeyframeTime)
imu_odom_end_index = i;
}
std::unique_ptr<CubicInterpolation> egovelIntegratorX;
std::unique_ptr<CubicInterpolation> egovelIntegratorY;
std::unique_ptr<CubicInterpolation> egovelIntegratorZ;
if (use_egovel_preinteg_trans) {
// integrate imu message from the beginning of this optimization
size_t twist_length = twist_queue.size();
Eigen::MatrixXd q_via_x(twist_length,3),q_via_y(twist_length,3),q_via_z(twist_length,3);
Eigen::VectorXd t_via_x(twist_length),t_via_y(twist_length),t_via_z(twist_length);
// double dt = 1.0/12;
for (size_t i=0; i < twist_length; i++){
q_via_x(i, 0) = twist_queue.at(i)->twist.linear.x; q_via_x(i, 1) = 0; q_via_x(i, 2) = 0;
// acc: q(i,1)=(twist_queue.at(i+1).twist.linear.x - twist_queue.at(i).twist.linear.x) / dt;
t_via_x(i) = twist_queue.at(i)->header.stamp.toSec();
q_via_y(i, 0) = twist_queue.at(i)->twist.linear.y; q_via_y(i, 1) = 0; q_via_y(i, 2) = 0;
t_via_y(i) = t_via_x(i);
q_via_z(i, 0) = twist_queue.at(i)->twist.linear.z; q_via_z(i, 1) = 0; q_via_z(i, 2) = 0;
t_via_z(i) = t_via_x(i);
}
egovelIntegratorX.reset(new CubicInterpolation(q_via_x, t_via_x)); // Integrator of ego velocity at X axis
egovelIntegratorY.reset(new CubicInterpolation(q_via_y, t_via_y)); // Integrator of ego velocity at Y axis
egovelIntegratorZ.reset(new CubicInterpolation(q_via_z, t_via_z)); // Integrator of ego velocity at Z axis
// ROS_INFO("Twist queue - Start time: %f Stop time: %f", t_via_x(0), t_via_x(t_via_x.size()-1));
}
Eigen::Isometry3d isom_imu_odom_last(Eigen::Isometry3d::Identity());
Eigen::Quaterniond q_imu_odom(imu_odom_queue.front()->pose.pose.orientation.w,
imu_odom_queue.front()->pose.pose.orientation.x,
imu_odom_queue.front()->pose.pose.orientation.y,
imu_odom_queue.front()->pose.pose.orientation.z);
isom_imu_odom_last.rotate(q_imu_odom);
isom_imu_odom_last.pretranslate(Eigen::Vector3d(imu_odom_queue.front()->pose.pose.position.x,
imu_odom_queue.front()->pose.pose.position.y,
imu_odom_queue.front()->pose.pose.position.z));
Eigen::Isometry3d isom_imu_odom_this(Eigen::Isometry3d::Identity());
q_imu_odom = Eigen::Quaterniond(imu_odom_queue.at(imu_odom_end_index)->pose.pose.orientation.w,
imu_odom_queue.at(imu_odom_end_index)->pose.pose.orientation.x,
imu_odom_queue.at(imu_odom_end_index)->pose.pose.orientation.y,
imu_odom_queue.at(imu_odom_end_index)->pose.pose.orientation.z);
isom_imu_odom_this.rotate(q_imu_odom);
isom_imu_odom_this.pretranslate(Eigen::Vector3d(imu_odom_queue.at(imu_odom_end_index)->pose.pose.position.x,
imu_odom_queue.at(imu_odom_end_index)->pose.pose.position.y,
imu_odom_queue.at(imu_odom_end_index)->pose.pose.position.z));
Eigen::Isometry3d isom_imu_odom_btn = isom_imu_odom_last.inverse() * isom_imu_odom_this;
// cout << isom_imu_odom_btn.matrix() << endl;
// ROS_INFO("IMU Odom queue - Start time: %f Stop time: %f", imu_odom_queue.at(0)->header.stamp.toSec(), imu_odom_queue.at(imu_odom_end_index)->header.stamp.toSec());
if (use_egovel_preinteg_trans){ // Use Ego vel as translation integration
for (size_t i = 0; i < imu_odom_end_index + 1; i++)
{
nav_msgs::Odometry::ConstPtr thisImu = imu_odom_queue.at(i);
double imuOdomTime = thisImu->header.stamp.toSec();
isometry_translation.setIdentity();
isometry_rotation.setIdentity();
double dt = (lastImuOdomQT < 0) ? (1.0 / 200.0) :(imuOdomTime - lastImuOdomQT);
Eigen::Vector3d translation_ = Eigen::Vector3d( egovelIntegratorX->getPosition(imuOdomTime),
egovelIntegratorY->getPosition(imuOdomTime),
egovelIntegratorZ->getPosition(imuOdomTime))* dt;
isometry_translation.pretranslate(translation_); // Set translation
isom_frame2frame = isom_frame2frame.pretranslate(isometry_translation.translation());
lastImuOdomQT = imuOdomTime;
}
}
else { // Use IMU as translation integration
isom_frame2frame = isom_imu_odom_btn;
}
translation_frame2frame.x = isom_frame2frame.translation().x();
translation_frame2frame.y = isom_frame2frame.translation().y();
translation_frame2frame.z = isom_frame2frame.translation().z();
const auto& last_imu_orien = imu_odom_queue.at(imu_odom_end_index);
trans_.rotation = last_imu_orien->pose.pose.orientation;
trans_.translation = translation_frame2frame;
}
return trans_;
}
void barometer_callback(const barometer_bmp388::BarometerPtr& baro_msg) {
if(!enable_barometer) {
return;
}
std::lock_guard<std::mutex> lock(barometer_queue_mutex);
barometer_queue.push_back(baro_msg);
}
bool flush_barometer_queue() {
std::lock_guard<std::mutex> lock(barometer_queue_mutex);
if(keyframes.empty() || barometer_queue.empty()) {
return false;
}
bool updated = false;
auto barometer_cursor = barometer_queue.begin();
for(size_t i=0; i < keyframes.size(); i++) {
auto keyframe = keyframes.at(i);
if(keyframe->stamp > barometer_queue.back()->header.stamp) {
break;
}
if(keyframe->stamp < (*barometer_cursor)->header.stamp || keyframe->altitude) {
continue;
}
// find the barometer data which is closest to the keyframe_
auto closest_barometer = barometer_cursor;
for(auto baro = barometer_cursor; baro != barometer_queue.end(); baro++) {
auto dt = ((*closest_barometer)->header.stamp - keyframe->stamp).toSec();
auto dt2 = ((*baro)->header.stamp - keyframe->stamp).toSec();
if(std::abs(dt) < std::abs(dt2)) {
break;
}
closest_barometer = baro;
}
// if the time residual between the barometer and keyframe_ is too large, skip it
barometer_cursor = closest_barometer;
if(0.2 < std::abs(((*closest_barometer)->header.stamp - keyframe->stamp).toSec())) {
continue;
}
Eigen::Vector4d aftmapped_pos(keyframe->odom_scan2scan.translation().x(), keyframe->odom_scan2scan.translation().y(), (*closest_barometer)->altitude, 1.0);
aftmapped_pos = initial_pose * aftmapped_pos;
// std::cout << "baro position: " << aftmapped_pos(0) << ", " << aftmapped_pos(1) << ", " << aftmapped_pos(2) << std::endl;
nav_msgs::Odometry initial_odom; // Initial posture
initial_odom = matrix2odom(keyframe->stamp, initial_pose, mapFrame, baselinkFrame);
Eigen::Vector1d z(aftmapped_pos(2));
// the first barometer data position will be the origin of the map
if(!zero_alt) {
zero_alt = z;
}
z -= (*zero_alt);
keyframe->altitude = z;
if (enable_barometer){
//********** G2O Edge ***********
if (barometer_edge_type == 1){
g2o::OptimizableGraph::Edge* edge;
Eigen::Vector1d information_matrix = Eigen::Vector1d::Identity() / barometer_edge_stddev;
edge = graph_slam->add_se3_prior_z_edge(keyframe->node, z, information_matrix);
graph_slam->add_robust_kernel(edge, private_nh.param<std::string>("barometer_edge_robust_kernel", "NONE"), private_nh.param<double>("barometer_edge_robust_kernel_size", 1.0));
}
else if (barometer_edge_type == 2 && i != 0 && keyframes.at(i-1)->altitude.is_initialized()){
g2o::OptimizableGraph::Edge* edge;
Eigen::Vector1d information_matrix = Eigen::Vector1d::Identity() / barometer_edge_stddev;
Eigen::Vector1d relative_z(keyframe->altitude.value() - keyframes.at(i-1)->altitude.value());
edge = graph_slam->add_se3_z_edge(keyframe->node, keyframes.at(i-1)->node, relative_z, information_matrix);
graph_slam->add_robust_kernel(edge, private_nh.param<std::string>("barometer_edge_robust_kernel", "NONE"), private_nh.param<double>("barometer_edge_robust_kernel_size", 1.0));
}
}
updated = true;
}
auto remove_loc = std::upper_bound(barometer_queue.begin(), barometer_queue.end(), keyframes.back()->stamp, [=](const ros::Time& stamp, const barometer_bmp388::BarometerConstPtr& baropoint) { return stamp < baropoint->header.stamp; });
barometer_queue.erase(barometer_queue.begin(), remove_loc);
return updated;
}
/**
* @brief this method adds all the keyframes_ in #keyframe_queue to the pose graph (odometry edges)
* @return if true, at least one keyframe_ was added to the pose graph
*/
bool flush_keyframe_queue() {
std::lock_guard<std::mutex> lock(keyframe_queue_mutex);
if(keyframe_queue.empty()) {
return false;
}
trans_odom2map_mutex.lock();
Eigen::Isometry3d odom2map(trans_odom2map.cast<double>());
trans_odom2map_mutex.unlock();
int num_processed = 0;
// ********** Select number of keyframess to be optimized **********
for(int i = 0; i < std::min<int>(keyframe_queue.size(), max_keyframes_per_update); i++) {
num_processed = i;
const auto& keyframe = keyframe_queue[i];
// new_keyframess will be tested later for loop closure
new_keyframes.push_back(keyframe);
// add pose node
Eigen::Isometry3d odom = odom2map * keyframe->odom_scan2scan;
// ********** Vertex of keyframess is contructed here ***********
keyframe->node = graph_slam->add_se3_node(odom);
keyframe_hash[keyframe->stamp] = keyframe;
// fix the first node
if(keyframes.empty() && new_keyframes.size() == 1) {
if(private_nh.param<bool>("fix_first_node", false)) {
Eigen::MatrixXd inf = Eigen::MatrixXd::Identity(6, 6);
std::stringstream sst(private_nh.param<std::string>("fix_first_node_stddev", "1 1 1 1 1 1"));
for(int i = 0; i < 6; i++) {
double stddev = 1.0;
sst >> stddev;
inf(i, i) = 1.0 / stddev;
}
anchor_node = graph_slam->add_se3_node(Eigen::Isometry3d::Identity());
anchor_node->setFixed(true);
anchor_edge = graph_slam->add_se3_edge(anchor_node, keyframe->node, Eigen::Isometry3d::Identity(), inf);
}
}
if(i == 0 && keyframes.empty()) {
continue;
}
/***** Scan-to-Scan Add edge to between consecutive keyframes *****/
const auto& prev_keyframe = i == 0 ? keyframes.back() : keyframe_queue[i - 1];
// relative pose between odom of previous frame and this frame R2=R12*R1 => R12 = inv(R2) * R1
Eigen::Isometry3d relative_pose = keyframe->odom_scan2scan.inverse() * prev_keyframe->odom_scan2scan;
// calculate fitness score as information
Eigen::MatrixXd information = inf_calclator->calc_information_matrix(keyframe->cloud, prev_keyframe->cloud, relative_pose);
auto edge = graph_slam->add_se3_edge(keyframe->node, prev_keyframe->node, relative_pose, information);
// cout << information << endl;
graph_slam->add_robust_kernel(edge, private_nh.param<std::string>("odometry_edge_robust_kernel", "NONE"), private_nh.param<double>("odometry_edge_robust_kernel_size", 1.0));
if (enable_preintegration){
// Add Preintegration edge
geometry_msgs::Transform relative_trans = keyframe->trans_integrated;
g2o::SE3Quat relative_se3quat ( Eigen::Quaterniond(relative_trans.rotation.w, relative_trans.rotation.x, relative_trans.rotation.y, relative_trans.rotation.z),
Eigen::Vector3d(relative_trans.translation.x, relative_trans.translation.y, relative_trans.translation.z));
Eigen::Isometry3d relative_isometry = transform2isometry(relative_trans);
Eigen::MatrixXd information_integ = Eigen::MatrixXd::Identity(6, 6);
information_integ << 1.0 / preinteg_trans_stddev, 0, 0, 0, 0, 0,
0, 1.0 / preinteg_trans_stddev, 0, 0, 0, 0,
0, 0, 1.0 / preinteg_trans_stddev, 0, 0, 0,
0, 0, 0, 1.0 / preinteg_orient_stddev, 0, 0,
0, 0, 0, 0, 1.0 / preinteg_orient_stddev, 0,
0, 0, 0, 0, 0, 1.0 / preinteg_orient_stddev;
auto edge_integ = graph_slam->add_se3_edge(prev_keyframe->node, keyframe->node, relative_isometry, information_integ);
graph_slam->add_robust_kernel(edge_integ, private_nh.param<std::string>("integ_edge_robust_kernel", "NONE"), private_nh.param<double>("integ_edge_robust_kernel_size", 1.0));
}
}
std_msgs::Header read_until;
read_until.stamp = keyframe_queue[num_processed]->stamp + ros::Duration(10, 0);
read_until.frame_id = points_topic;
read_until_pub.publish(read_until);
read_until.frame_id = "/filtered_points";
read_until_pub.publish(read_until);
keyframe_queue.erase(keyframe_queue.begin(), keyframe_queue.begin() + num_processed + 1);
return true;
}
/**
* @brief Back-end Optimization. This methods adds all the data in the queues to the pose graph, and then optimizes the pose graph
* @param event
*/
void optimization_timer_callback(const ros::WallTimerEvent& event) {
std::lock_guard<std::mutex> lock(main_thread_mutex);
// add keyframes_ and floor coeffs in the queues to the pose graph
bool keyframe_updated = flush_keyframe_queue();
if(!keyframe_updated) {
std_msgs::Header read_until;
read_until.stamp = ros::Time::now() + ros::Duration(30, 0);
read_until.frame_id = points_topic;
read_until_pub.publish(read_until);
read_until.frame_id = "/filtered_points";
read_until_pub.publish(read_until);
}
if(!keyframe_updated & !flush_gps_queue() & !flush_barometer_queue()) {
return;
}
// loop detection
if(private_nh.param<bool>("enable_loop_closure", false)){
std::vector<Loop::Ptr> loops = loop_detector->detect(keyframes, new_keyframes, *graph_slam);
}
// Copy "new_keyframes_" to vector "keyframes_", "new_keyframes_" was used for loop detaction
std::copy(new_keyframes.begin(), new_keyframes.end(), std::back_inserter(keyframes));
new_keyframes.clear();
if(private_nh.param<bool>("enable_loop_closure", false))
addLoopFactor();
// move the first node / position to the current estimate of the first node pose
// so the first node moves freely while trying to stay around the origin
if(anchor_node && private_nh.param<bool>("fix_first_node_adaptive", true)) {
Eigen::Isometry3d anchor_target = static_cast<g2o::VertexSE3*>(anchor_edge->vertices()[1])->estimate();
anchor_node->setEstimate(anchor_target);
}
// optimize the pose graph
int num_iterations = private_nh.param<int>("g2o_solver_num_iterations", 1024);
clock_t start_ms = clock();
graph_slam->optimize(num_iterations);
clock_t end_ms = clock();
double time_used = double(end_ms - start_ms) / CLOCKS_PER_SEC;
opt_time.push_back(time_used);
//********** publish tf **********
const auto& keyframe = keyframes.back();
// RadarOdom_to_base = map_to_base * map_to_RadarOdom^(-1)
Eigen::Isometry3d trans = keyframe->node->estimate() * keyframe->odom_scan2scan.inverse();
Eigen::Isometry3d map2base_trans = keyframe->node->estimate();
trans_odom2map_mutex.lock();
trans_odom2map = trans.matrix();
// map2base_incremental = map2base_last^(-1) * map2base_this
trans_aftmapped_incremental = trans_aftmapped.inverse() * map2base_trans;
trans_aftmapped = map2base_trans;
trans_odom2map_mutex.unlock();
std::vector<KeyFrameSnapshot::Ptr> snapshot(keyframes.size());
std::transform(keyframes.begin(), keyframes.end(), snapshot.begin(), [=](const KeyFrame::Ptr& k) { return std::make_shared<KeyFrameSnapshot>(k); });
keyframes_snapshot_mutex.lock();
keyframes_snapshot.swap(snapshot);
keyframes_snapshot_mutex.unlock();
graph_updated = true;
// Publish After-Mapped Odometry
nav_msgs::Odometry aft = isometry2odom(keyframe->stamp, trans_aftmapped, mapFrame, odometryFrame);
aftmapped_odom_pub.publish(aft);
// Publish After-Mapped Odometry Incrementation
nav_msgs::Odometry aft_incre = isometry2odom(keyframe->stamp, trans_aftmapped_incremental, mapFrame, odometryFrame);
aftmapped_odom_incremenral_pub.publish(aft_incre);
// Publish /odom to /base_link
if(odom2base_pub.getNumSubscribers()) { // Returns the number of subscribers that are currently connected to this Publisher
geometry_msgs::TransformStamped ts = matrix2transform(keyframe->stamp, trans.matrix(), mapFrame, odometryFrame);
odom2base_pub.publish(ts);
}
if(markers_pub.getNumSubscribers()) {
auto markers = create_marker_array(ros::Time::now());
markers_pub.publish(markers);
}
}
void addLoopFactor()
{
if (loop_detector->loopIndexQueue.empty())
return;
for (int i = 0; i < (int)loop_detector->loopIndexQueue.size(); ++i){
int indexFrom = loop_detector->loopIndexQueue[i].first;
int indexTo = loop_detector->loopIndexQueue[i].second;
Eigen::Isometry3d poseBetween = loop_detector->loopPoseQueue[i];
Eigen::MatrixXd information_matrix = loop_detector->loopInfoQueue[i];
auto edge = graph_slam->add_se3_edge(keyframes[indexFrom]->node, keyframes[indexTo]->node, poseBetween, information_matrix);
graph_slam->add_robust_kernel(edge, private_nh.param<std::string>("loop_closure_edge_robust_kernel", "NONE"), private_nh.param<double>("loop_closure_edge_robust_kernel_size", 1.0));
}
// loopIndexQueue.clear();
// loopPoseQueue.clear();
// loopInfoQueue.clear();
// aLoopIsClosed = true;
}
/**
* @brief generate map point cloud and publish it
* @param event
*/
void map_points_publish_timer_callback(const ros::WallTimerEvent& event) {
if(!map_points_pub.getNumSubscribers() || !graph_updated) {
return;
}
std::vector<KeyFrameSnapshot::Ptr> snapshot;
keyframes_snapshot_mutex.lock();
snapshot = keyframes_snapshot;
keyframes_snapshot_mutex.unlock();
auto cloud = map_cloud_generator->generate(snapshot, map_cloud_resolution);
if(!cloud) {
return;
}
cloud->header.frame_id = mapFrame;
cloud->header.stamp = snapshot.back()->cloud->header.stamp;
sensor_msgs::PointCloud2Ptr cloud_msg(new sensor_msgs::PointCloud2());
pcl::toROSMsg(*cloud, *cloud_msg);
map_points_pub.publish(cloud_msg);
}
/**
* @brief create visualization marker
* @param stamp
* @return
*/
visualization_msgs::MarkerArray create_marker_array(const ros::Time& stamp) const {
visualization_msgs::MarkerArray markers;
if (show_sphere)
markers.markers.resize(5);
else
markers.markers.resize(4);
// loop edges
visualization_msgs::Marker& loop_marker = markers.markers[0];
loop_marker.header.frame_id = "map";
loop_marker.header.stamp = stamp;
loop_marker.action = visualization_msgs::Marker::ADD;
loop_marker.type = visualization_msgs::Marker::LINE_LIST;
loop_marker.ns = "loop_edges";
loop_marker.id = 1;
loop_marker.pose.orientation.w = 1;
loop_marker.scale.x = 0.1; loop_marker.scale.y = 0.1; loop_marker.scale.z = 0.1;
loop_marker.color.r = 0.9; loop_marker.color.g = 0.9; loop_marker.color.b = 0;
loop_marker.color.a = 1;
for (auto it = loop_detector->loopIndexContainer.begin(); it != loop_detector->loopIndexContainer.end(); ++it)
{
int key_cur = it->first;
int key_pre = it->second;
geometry_msgs::Point p;
Eigen::Vector3d pos = keyframes[key_cur]->node->estimate().translation();
p.x = pos.x();
p.y = pos.y();
p.z = pos.z();
loop_marker.points.push_back(p);
pos = keyframes[key_pre]->node->estimate().translation();
p.x = pos.x();
p.y = pos.y();
p.z = pos.z();
loop_marker.points.push_back(p);
}
// node markers
visualization_msgs::Marker& traj_marker = markers.markers[1];
traj_marker.header.frame_id = "map";
traj_marker.header.stamp = stamp;
traj_marker.ns = "nodes";
traj_marker.id = 0;
traj_marker.type = visualization_msgs::Marker::SPHERE_LIST;
traj_marker.pose.orientation.w = 1.0;
traj_marker.scale.x = traj_marker.scale.y = traj_marker.scale.z = 0.3;
visualization_msgs::Marker& imu_marker = markers.markers[2];
imu_marker.header = traj_marker.header;
imu_marker.ns = "imu";
imu_marker.id = 1;
imu_marker.type = visualization_msgs::Marker::SPHERE_LIST;
imu_marker.pose.orientation.w = 1.0;
imu_marker.scale.x = imu_marker.scale.y = imu_marker.scale.z = 0.75;
traj_marker.points.resize(keyframes.size());
traj_marker.colors.resize(keyframes.size());
for(size_t i = 0; i < keyframes.size(); i++) {
Eigen::Vector3d pos = keyframes[i]->node->estimate().translation();
traj_marker.points[i].x = pos.x();
traj_marker.points[i].y = pos.y();
traj_marker.points[i].z = pos.z();
double p = static_cast<double>(i) / keyframes.size();
traj_marker.colors[i].r = 0.0;//1.0 - p;
traj_marker.colors[i].g = 1.0;//p;
traj_marker.colors[i].b = 0.0;
traj_marker.colors[i].a = 1.0;
if(keyframes[i]->acceleration) {
Eigen::Vector3d pos = keyframes[i]->node->estimate().translation();
geometry_msgs::Point point;
point.x = pos.x();
point.y = pos.y();
point.z = pos.z();
std_msgs::ColorRGBA color;
color.r = 0.0;
color.g = 0.0;
color.b = 1.0;
color.a = 0.1;
imu_marker.points.push_back(point);
imu_marker.colors.push_back(color);
}
}
// edge markers
visualization_msgs::Marker& edge_marker = markers.markers[3];
edge_marker.header.frame_id = "map";
edge_marker.header.stamp = stamp;
edge_marker.ns = "edges";
edge_marker.id = 2;
edge_marker.type = visualization_msgs::Marker::LINE_LIST;
edge_marker.pose.orientation.w = 1.0;
edge_marker.scale.x = 0.05;
edge_marker.points.resize(graph_slam->graph->edges().size() * 2);
edge_marker.colors.resize(graph_slam->graph->edges().size() * 2);
auto edge_itr = graph_slam->graph->edges().begin();
for(int i = 0; edge_itr != graph_slam->graph->edges().end(); edge_itr++, i++) {
g2o::HyperGraph::Edge* edge = *edge_itr;
g2o::EdgeSE3* edge_se3 = dynamic_cast<g2o::EdgeSE3*>(edge);
if(edge_se3) {
g2o::VertexSE3* v1 = dynamic_cast<g2o::VertexSE3*>(edge_se3->vertices()[0]);
g2o::VertexSE3* v2 = dynamic_cast<g2o::VertexSE3*>(edge_se3->vertices()[1]);
Eigen::Vector3d pt1 = v1->estimate().translation();
Eigen::Vector3d pt2 = v2->estimate().translation();
edge_marker.points[i * 2].x = pt1.x();
edge_marker.points[i * 2].y = pt1.y();
edge_marker.points[i * 2].z = pt1.z();
edge_marker.points[i * 2 + 1].x = pt2.x();
edge_marker.points[i * 2 + 1].y = pt2.y();
edge_marker.points[i * 2 + 1].z = pt2.z();
double p1 = static_cast<double>(v1->id()) / graph_slam->graph->vertices().size();
double p2 = static_cast<double>(v2->id()) / graph_slam->graph->vertices().size();
edge_marker.colors[i * 2].r = 0.0;//1.0 - p1;
edge_marker.colors[i * 2].g = 1.0;//p1;
edge_marker.colors[i * 2].a = 1.0;
edge_marker.colors[i * 2 + 1].r = 0.0;//1.0 - p2;
edge_marker.colors[i * 2 + 1].g = 1.0;//p2;
edge_marker.colors[i * 2 + 1].a = 1.0;
if(std::abs(v1->id() - v2->id()) > 2) {
// edge_marker.points[i * 2].z += 0.5;
// edge_marker.points[i * 2 + 1].z += 0.5;
edge_marker.colors[i * 2].r = 0.9;
edge_marker.colors[i * 2].g = 0.9;
edge_marker.colors[i * 2].b = 0.0;
edge_marker.colors[i * 2 + 1].r = 0.9;
edge_marker.colors[i * 2 + 1].g = 0.9;
edge_marker.colors[i * 2 + 1].b = 0.0;
edge_marker.colors[i * 2].a = 0.0;
edge_marker.colors[i * 2 + 1].a += 0.0;
}
continue;
}
g2o::EdgeSE3Plane* edge_plane = dynamic_cast<g2o::EdgeSE3Plane*>(edge);
if(edge_plane) {
g2o::VertexSE3* v1 = dynamic_cast<g2o::VertexSE3*>(edge_plane->vertices()[0]);
Eigen::Vector3d pt1 = v1->estimate().translation();
Eigen::Vector3d pt2(pt1.x(), pt1.y(), 0.0);
edge_marker.points[i * 2].x = pt1.x();
edge_marker.points[i * 2].y = pt1.y();
edge_marker.points[i * 2].z = pt1.z();
edge_marker.points[i * 2 + 1].x = pt2.x();
edge_marker.points[i * 2 + 1].y = pt2.y();
edge_marker.points[i * 2 + 1].z = pt2.z();
edge_marker.colors[i * 2].b = 1.0;
edge_marker.colors[i * 2].a = 1.0;
edge_marker.colors[i * 2 + 1].b = 1.0;
edge_marker.colors[i * 2 + 1].a = 1.0;
continue;
}
g2o::EdgeSE3PriorXY* edge_priori_xy = dynamic_cast<g2o::EdgeSE3PriorXY*>(edge);
if(edge_priori_xy) {
g2o::VertexSE3* v1 = dynamic_cast<g2o::VertexSE3*>(edge_priori_xy->vertices()[0]);
Eigen::Vector3d pt1 = v1->estimate().translation();
Eigen::Vector3d pt2 = Eigen::Vector3d::Zero();
pt2.head<2>() = edge_priori_xy->measurement();
edge_marker.points[i * 2].x = pt1.x();
edge_marker.points[i * 2].y = pt1.y();
edge_marker.points[i * 2].z = pt1.z() + 0.5;
edge_marker.points[i * 2 + 1].x = pt2.x();
edge_marker.points[i * 2 + 1].y = pt2.y();
edge_marker.points[i * 2 + 1].z = pt2.z() + 0.5;
edge_marker.colors[i * 2].r = 1.0;
edge_marker.colors[i * 2].a = 1.0;
edge_marker.colors[i * 2 + 1].r = 1.0;
edge_marker.colors[i * 2 + 1].a = 1.0;
continue;
}
g2o::EdgeSE3PriorXYZ* edge_priori_xyz = dynamic_cast<g2o::EdgeSE3PriorXYZ*>(edge);
if(edge_priori_xyz) {
g2o::VertexSE3* v1 = dynamic_cast<g2o::VertexSE3*>(edge_priori_xyz->vertices()[0]);
Eigen::Vector3d pt1 = v1->estimate().translation();
Eigen::Vector3d pt2 = edge_priori_xyz->measurement();
edge_marker.points[i * 2].x = pt1.x();
edge_marker.points[i * 2].y = pt1.y();
edge_marker.points[i * 2].z = pt1.z() + 0.5;
edge_marker.points[i * 2 + 1].x = pt2.x();
edge_marker.points[i * 2 + 1].y = pt2.y();
edge_marker.points[i * 2 + 1].z = pt2.z();
edge_marker.colors[i * 2].r = 1.0;
edge_marker.colors[i * 2].a = 1.0;
edge_marker.colors[i * 2 + 1].r = 1.0;
edge_marker.colors[i * 2 + 1].a = 1.0;
continue;
}
}
if (show_sphere)
{
// sphere
visualization_msgs::Marker& sphere_marker = markers.markers[4];
sphere_marker.header.frame_id = "map";
sphere_marker.header.stamp = stamp;
sphere_marker.ns = "loop_close_radius";
sphere_marker.id = 3;
sphere_marker.type = visualization_msgs::Marker::SPHERE;
if(!keyframes.empty()) {
Eigen::Vector3d pos = keyframes.back()->node->estimate().translation();
sphere_marker.pose.position.x = pos.x();
sphere_marker.pose.position.y = pos.y();
sphere_marker.pose.position.z = pos.z();
}
sphere_marker.pose.orientation.w = 1.0;
sphere_marker.scale.x = sphere_marker.scale.y = sphere_marker.scale.z = loop_detector->get_distance_thresh() * 2.0;
sphere_marker.color.r = 1.0;
sphere_marker.color.a = 0.3;
}
return markers;
}
/**
* @brief dump all data to the current directory
* @param req
* @param res
* @return
*/
bool dump_service(radar_graph_slam::DumpGraphRequest& req, radar_graph_slam::DumpGraphResponse& res) {
std::lock_guard<std::mutex> lock(main_thread_mutex);
std::string directory = req.destination;
if(directory.empty()) {
std::array<char, 64> buffer;
buffer.fill(0);
time_t rawtime;
time(&rawtime);
const auto timeinfo = localtime(&rawtime);
strftime(buffer.data(), sizeof(buffer), "%d-%m-%Y %H:%M:%S", timeinfo);
}
if(!boost::filesystem::is_directory(directory)) {
boost::filesystem::create_directory(directory);
}
std::cout << "all data dumped to:" << directory << std::endl;
graph_slam->save(directory + "/graph.g2o");
for(size_t i = 0; i < keyframes.size(); i++) {
std::stringstream sst;
sst << boost::format("%s/%06d") % directory % i;
keyframes[i]->save(sst.str());
}
if(zero_utm) {
std::ofstream zero_utm_ofs(directory + "/zero_utm");
zero_utm_ofs << boost::format("%.6f %.6f %.6f") % zero_utm->x() % zero_utm->y() % zero_utm->z() << std::endl;
}
std::ofstream ofs(directory + "/special_nodes.csv");
ofs << "anchor_node " << (anchor_node == nullptr ? -1 : anchor_node->id()) << std::endl;
ofs << "anchor_edge " << (anchor_edge == nullptr ? -1 : anchor_edge->id()) << std::endl;
ofs << "floor_node " << (floor_plane_node == nullptr ? -1 : floor_plane_node->id()) << std::endl;
res.success = true;
return true;
}
/**
* @brief save map data as pcd
* @param req
* @param res
* @return
*/
bool save_map_service(radar_graph_slam::SaveMapRequest& req, radar_graph_slam::SaveMapResponse& res) {
std::vector<KeyFrameSnapshot::Ptr> snapshot;
keyframes_snapshot_mutex.lock();
snapshot = keyframes_snapshot;
keyframes_snapshot_mutex.unlock();
auto cloud = map_cloud_generator->generate(snapshot, req.resolution);
if(!cloud) {
res.success = false;
return true;
}
if(zero_utm && req.utm) {
for(auto& pt : cloud->points) {
pt.getVector3fMap() += (*zero_utm).cast<float>();
}
}
cloud->header.frame_id = mapFrame;
cloud->header.stamp = snapshot.back()->cloud->header.stamp;
if(zero_utm) {
std::ofstream ofs(req.destination + ".utm");
ofs << boost::format("%.6f %.6f %.6f") % zero_utm->x() % zero_utm->y() % zero_utm->z() << std::endl;
}
int ret = pcl::io::savePCDFileBinary(req.destination, *cloud);
res.success = ret == 0;
return true;
}
void nmea_callback(const nmea_msgs::SentenceConstPtr& nmea_msg) {
GPRMC grmc = nmea_parser->parse(nmea_msg->sentence);
if(grmc.status != 'A')
return;
geographic_msgs::GeoPointStampedPtr gps_msg(new geographic_msgs::GeoPointStamped());
gps_msg->header = nmea_msg->header;
gps_msg->position.latitude = grmc.latitude;
gps_msg->position.longitude = grmc.longitude;
gps_msg->position.altitude = NAN;
gps_callback(gps_msg);
}
void navsat_callback(const sensor_msgs::NavSatFixConstPtr& navsat_msg) {
sensor_msgs::NavSatFix gps_msg;
gps_msg.header = navsat_msg->header;
gps_msg.latitude = navsat_msg->latitude;
gps_msg.longitude = navsat_msg->longitude;
gps_msg.altitude = navsat_msg->altitude;
gps_msg.position_covariance = navsat_msg->position_covariance;
gps_msg.position_covariance_type = navsat_msg->position_covariance_type;
gps_msg.status = navsat_msg->status;
gps_navsat_queue.push_back(gps_msg);
}
/**
* @brief received gps data is added to #gps_queue_
* @param gps_msg
*/
void gps_callback(const geographic_msgs::GeoPointStampedPtr& gps_msg) {
std::lock_guard<std::mutex> lock(gps_queue_mutex);
gps_msg->header.stamp += ros::Duration(gps_time_offset);
gps_geopoint_queue.push_back(gps_msg);
}
/**
* @brief
* @return
*/
bool flush_gps_queue() {
std::lock_guard<std::mutex> lock(gps_queue_mutex);
if(keyframes.empty() || gps_navsat_queue.empty()) {
return false;
}
bool updated = false;
auto gps_cursor = gps_navsat_queue.begin();
for(auto& keyframe : keyframes) {
if (keyframe->index - last_gps_edge_index < gps_edge_intervals) continue;
if (keyframe->stamp > gps_navsat_queue.back().header.stamp) {
break;
}
if (keyframe->stamp < (*gps_cursor).header.stamp || keyframe->utm_coord) {
continue;
}
// find the gps data which is closest to the keyframe_
auto closest_gps = gps_cursor;
for(auto gps = gps_cursor; gps != gps_navsat_queue.end(); gps++) {
auto dt = ((*closest_gps).header.stamp - keyframe->stamp).toSec();
auto dt2 = ((*gps).header.stamp - keyframe->stamp).toSec();
if(std::abs(dt) < std::abs(dt2)) {
break;
}
closest_gps = gps;
}
// if the time residual between the gps and keyframe_ is too large, skip it
gps_cursor = closest_gps;
if(0.2 < std::abs(((*closest_gps).header.stamp - keyframe->stamp).toSec())) {
continue;
}
// convert (latitude, longitude, altitude) -> (easting, northing, altitude) in UTM coordinate
geographic_msgs::GeoPoint gps_geopoint;
gps_geopoint.altitude = (*closest_gps).altitude;
gps_geopoint.latitude = (*closest_gps).latitude;
gps_geopoint.longitude = (*closest_gps).longitude;
geodesy::UTMPoint utm;
geodesy::fromMsg(gps_geopoint, utm);
Eigen::Vector3d xyz(utm.easting, utm.northing, utm.altitude);
double cov_x = (*closest_gps).position_covariance.at(0);
double cov_y = (*closest_gps).position_covariance.at(4);
double cov_z = (*closest_gps).position_covariance.at(8);
if (cov_x > max_gps_edge_stddev_xy || cov_y > max_gps_edge_stddev_xy || cov_z > max_gps_edge_stddev_z)
continue;
// the first gps data position will be the origin of the map
// if(!zero_utm) {
// zero_utm = xyz;
// }
// xyz -= (*zero_utm);
keyframe->utm_coord = xyz;
Eigen::Vector3d world_coordinate = (utm_to_world * Eigen::Vector4d(utm.easting, utm.northing, utm.altitude, 1)).head(3);
Eigen::Vector3d trans_err = keyframe->node->estimate().translation() - world_coordinate;
if (trans_err.norm() < 5.0) continue;
//********** G2O Edge ***********
g2o::OptimizableGraph::Edge* edge;
if(std::isnan(world_coordinate.z())) {
Eigen::Matrix2d information_matrix = Eigen::Matrix2d::Identity() / cov_x;
edge = graph_slam->add_se3_prior_xy_edge(keyframe->node, world_coordinate.head<2>(), information_matrix);
} else {
Eigen::Matrix3d information_matrix = Eigen::Matrix3d::Identity();
information_matrix(0, 0) /= cov_x;
information_matrix(1, 1) /= cov_y;
information_matrix(2, 2) /= cov_z;
edge = graph_slam->add_se3_prior_xyz_edge(keyframe->node, world_coordinate, information_matrix);
}
graph_slam->add_robust_kernel(edge, private_nh.param<std::string>("gps_edge_robust_kernel", "NONE"), private_nh.param<double>("gps_edge_robust_kernel_size", 1.0));
last_gps_edge_index = keyframe->index;
updated = true;
}
auto remove_loc = std::upper_bound(gps_navsat_queue.begin(), gps_navsat_queue.end(), keyframes.back()->stamp, [=](const ros::Time& stamp, const sensor_msgs::NavSatFix& geopoint) { return stamp < geopoint.header.stamp; });
gps_navsat_queue.erase(gps_navsat_queue.begin(), remove_loc);
return updated;
}
void command_callback(const std_msgs::String& str_msg) {
if (str_msg.data == "output_aftmapped") {
ofstream fout;
fout.open("/home/zhuge/stamped_pose_graph_estimate.txt", ios::out);
fout << "# timestamp tx ty tz qx qy qz qw" << endl;
fout.setf(ios::fixed, ios::floatfield); // fixed mode，float
fout.precision(8); // Set precision 8
for(size_t i = 0; i < keyframes.size(); i++) {
Eigen::Vector3d pos_ = keyframes[i]->node->estimate().translation();
Eigen::Matrix3d rot_ = keyframes[i]->node->estimate().rotation();
Eigen::Quaterniond quat_(rot_);
double timestamp = keyframes[i]->stamp.toSec();
double tx = pos_(0), ty = pos_(1), tz = pos_(2);
double qx = quat_.x(), qy = quat_.y(), qz = quat_.z(), qw = quat_.w();
fout << timestamp << " "
<< tx << " " << ty << " " << tz << " "
<< qx << " " << qy << " " << qz << " " << qw << endl;
}
fout.close();
ROS_INFO("Optimized edges have been output!");
}
else if (str_msg.data == "time") {
if (loop_detector->pf_time.size() > 0) {
std::sort(loop_detector->pf_time.begin(), loop_detector->pf_time.end());
double median = loop_detector->pf_time.at(floor((double)loop_detector->pf_time.size() / 2));
cout << "Pre-filtering Matching time cost (median): " << median << endl;
}
if (loop_detector->sc_time.size() > 0) {
std::sort(loop_detector->sc_time.begin(), loop_detector->sc_time.end());
double median = loop_detector->sc_time.at(floor((double)loop_detector->sc_time.size() / 2));
cout << "Scan Context time cost (median): " << median << endl;
}
if (loop_detector->oc_time.size() > 0) {
std::sort(loop_detector->oc_time.begin(), loop_detector->oc_time.end());
double median = loop_detector->oc_time.at(floor((double)loop_detector->oc_time.size() / 2));
cout << "Odometry Check time cost (median): " << median << endl;
}
if (opt_time.size() > 0) {
std::sort(opt_time.begin(), opt_time.end());
double median = opt_time.at(floor((double)opt_time.size() / 2));
cout << "Optimization time cost (median): " << median << endl;
}
}
}
private:
// ROS
ros::NodeHandle nh;
ros::NodeHandle mt_nh;
ros::NodeHandle private_nh;
ros::WallTimer optimization_timer;
ros::WallTimer map_publish_timer;
std::unique_ptr<message_filters::Subscriber<nav_msgs::Odometry>> odom_sub;
std::unique_ptr<message_filters::Subscriber<sensor_msgs::PointCloud2>> cloud_sub;
std::unique_ptr<message_filters::Synchronizer<ApproxSyncPolicy>> sync;
ros::Subscriber barometer_sub;
ros::Subscriber gps_sub;
ros::Subscriber nmea_sub;
ros::Subscriber navsat_sub;
ros::Subscriber imu_odom_sub;
ros::Subscriber imu_sub;
ros::Subscriber command_sub;
ros::Publisher imu_odom_pub;
ros::Publisher markers_pub;
std::mutex trans_odom2map_mutex;
Eigen::Matrix4d trans_odom2map; // keyframe->node->estimate() * keyframe->odom.inverse();
Eigen::Isometry3d trans_aftmapped; // Odometry from /map to /base_link
Eigen::Isometry3d trans_aftmapped_incremental;
ros::Publisher odom2base_pub;
ros::Publisher aftmapped_odom_pub;
ros::Publisher aftmapped_odom_incremenral_pub;
ros::Publisher odom_frame2frame_pub;
std::string points_topic;
ros::Publisher read_until_pub;
ros::Publisher map_points_pub;
tf::TransformListener tf_listener;
tf::TransformBroadcaster map2base_broadcaster; // odom_frame => base_frame
ros::ServiceServer dump_service_server;
ros::ServiceServer save_map_service_server;
// keyframe queue
std::mutex keyframe_queue_mutex;
std::deque<KeyFrame::Ptr> keyframe_queue;
std::deque<geometry_msgs::TwistStampedConstPtr> twist_queue;
std::deque<nav_msgs::OdometryConstPtr> imu_odom_queue;
double thisKeyframeTime;
double lastKeyframeTime;
size_t keyframe_index = 0;
// IMU / Ego Velocity Integration
bool enable_preintegration;
double preinteg_orient_stddev;
double preinteg_trans_stddev;
bool enable_imu_orientation;
bool use_egovel_preinteg_trans;
Eigen::Matrix4d initial_pose;
// barometer queue
bool enable_barometer;
int barometer_edge_type;
double barometer_edge_stddev;
boost::optional<Eigen::Vector1d> zero_alt;
std::mutex barometer_queue_mutex;
std::deque<barometer_bmp388::BarometerConstPtr> barometer_queue;
// gps queue
int gps_edge_intervals;
int last_gps_edge_index;
double gps_time_offset;
double gps_edge_stddev_xy;
double gps_edge_stddev_z;
double max_gps_edge_stddev_xy;
double max_gps_edge_stddev_z;
boost::optional<Eigen::Vector3d> zero_utm;
std::mutex gps_queue_mutex;
std::deque<geographic_msgs::GeoPointStampedConstPtr> gps_geopoint_queue;
std::deque<sensor_msgs::NavSatFix> gps_navsat_queue;
Eigen::Matrix4d utm_to_world;
std::string dataset_name;
// Marker coefficients
bool show_sphere;
// for map cloud generation
std::atomic_bool graph_updated;
double map_cloud_resolution;
std::mutex keyframes_snapshot_mutex;
std::vector<KeyFrameSnapshot::Ptr> keyframes_snapshot;
std::unique_ptr<MapCloudGenerator> map_cloud_generator;
// graph slam
// all the below members must be accessed after locking main_thread_mutex
std::mutex main_thread_mutex;
int max_keyframes_per_update;
// Used for Loop Closure detection source,
// pushed form keyframe_queue at "flush_keyframe_queue()",
// inserted to "keyframes_" before optimization
std::deque<KeyFrame::Ptr> new_keyframes;
// Previous keyframes_
std::vector<KeyFrame::Ptr> keyframes;
std::unordered_map<ros::Time, KeyFrame::Ptr, RosTimeHash> keyframe_hash;
g2o::VertexSE3* anchor_node;
g2o::EdgeSE3* anchor_edge;
g2o::VertexPlane* floor_plane_node;
std::unique_ptr<GraphSLAM> graph_slam;
std::unique_ptr<LoopDetector> loop_detector;
std::unique_ptr<KeyframeUpdater> keyframe_updater;
std::unique_ptr<NmeaSentenceParser> nmea_parser;
std::unique_ptr<InformationMatrixCalculator> inf_calclator;
// Registration Method
pcl::Registration<PointT, PointT>::Ptr registration;
pcl::KdTreeFLANN<PointT>::Ptr kdtreeHistoryKeyPoses;
std::vector<double> opt_time;
};
} // namespace radar_graph_slam
PLUGINLIB_EXPORT_CLASS(radar_graph_slam::RadarGraphSlamNodelet, nodelet::Nodelet)
================================================
FILE: apps/scan_matching_odometry_nodelet.cpp
================================================
// SPDX-License-Identifier: BSD-2-Clause
#include <ctime>
#include <chrono>
#include <mutex>
#include <atomic>
#include <memory>
#include <iomanip>
#include <iostream>
#include <cmath>
#include <unordered_map>
#include <boost/format.hpp>
#include <boost/thread.hpp>
#include <boost/filesystem.hpp>
#include <boost/algorithm/string.hpp>
#include <ros/ros.h>
#include <ros/time.h>
#include <ros/duration.h>
#include <tf_conversions/tf_eigen.h>
#include <tf/transform_listener.h>
#include <tf/transform_broadcaster.h>
#include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h>
#include <message_filters/synchronizer.h>
#include <message_filters/sync_policies/approximate_time.h>
#include <std_msgs/String.h>
#include <std_msgs/Time.h>
#include <nav_msgs/Odometry.h>
#include <sensor_msgs/PointCloud2.h>
#include <sensor_msgs/Imu.h>
#include <geometry_msgs/TransformStamped.h>
#include <geometry_msgs/PoseWithCovarianceStamped.h>
#include <geometry_msgs/TwistWithCovarianceStamped.h>
#include <nodelet/nodelet.h>
#include <pluginlib/class_list_macros.h>
#include <pcl_ros/point_cloud.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/passthrough.h>
#include <pcl/filters/approximate_voxel_grid.h>
#include <pcl/octree/octree_search.h>
#include <Eigen/Dense>
#include <radar_graph_slam/ros_utils.hpp>
#include <radar_graph_slam/registrations.hpp>
#include <radar_graph_slam/ScanMatchingStatus.h>
#include <radar_graph_slam/keyframe.hpp>
#include <radar_graph_slam/keyframe_updater.hpp>
#include <radar_graph_slam/graph_slam.hpp>
#include <radar_graph_slam/information_matrix_calculator.hpp>
#include "utility_radar.h"
using namespace std;
namespace radar_graph_slam {
class ScanMatchingOdometryNodelet : public nodelet::Nodelet, public ParamServer {
public:
typedef pcl::PointXYZI PointT;
typedef message_filters::sync_policies::ApproximateTime<geometry_msgs::TwistWithCovarianceStamped, sensor_msgs::PointCloud2> ApproxSyncPolicy;
// typedef message_filters::sync_policies::ApproximateTime<sensor_msgs::PointCloud2, geometry_msgs::TransformStamped> ApproxSyncPolicy2;
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
ScanMatchingOdometryNodelet() {}
virtual ~ScanMatchingOdometryNodelet() {}
virtual void onInit() {
NODELET_DEBUG("initializing scan_matching_odometry_nodelet...");
nh = getNodeHandle();
mt_nh = getMTNodeHandle();
private_nh = getPrivateNodeHandle();
initialize_params(); // this
if(private_nh.param<bool>("enable_imu_frontend", false)) {
msf_pose_sub = nh.subscribe<geometry_msgs::PoseWithCovarianceStamped>("/msf_core/pose", 1, boost::bind(&ScanMatchingOdometryNodelet::msf_pose_callback, this, _1, false));
msf_pose_after_update_sub = nh.subscribe<geometry_msgs::PoseWithCovarianceStamped>("/msf_core/pose_after_update", 1, boost::bind(&ScanMatchingOdometryNodelet::msf_pose_callback, this, _1, true));
}
//******** Subscribers **********
ego_vel_sub.reset(new message_filters::Subscriber<geometry_msgs::TwistWithCovarianceStamped>(mt_nh, "/eagle_data/twist", 256));
points_sub.reset(new message_filters::Subscriber<sensor_msgs::PointCloud2>(mt_nh, "/filtered_points", 32));
sync.reset(new message_filters::Synchronizer<ApproxSyncPolicy>(ApproxSyncPolicy(32), *ego_vel_sub, *points_sub));
sync->registerCallback(boost::bind(&ScanMatchingOdometryNodelet::pointcloud_callback, this, _1, _2));
imu_sub = nh.subscribe("/imu", 1024, &ScanMatchingOdometryNodelet::imu_callback, this);
command_sub = nh.subscribe("/command", 10, &ScanMatchingOdometryNodelet::command_callback, this);
//******** Publishers **********
read_until_pub = nh.advertise<std_msgs::Header>("/scan_matching_odometry/read_until", 32);
// Odometry of Radar scan-matching_
odom_pub = nh.advertise<nav_msgs::Odometry>(odomTopic, 32);
// Transformation of Radar scan-matching_
trans_pub = nh.advertise<geometry_msgs::TransformStamped>("/scan_matching_odometry/transform", 32);
status_pub = private_nh.advertise<ScanMatchingStatus>("/scan_matching_odometry/status", 8);
aligned_points_pub = nh.advertise<sensor_msgs::PointCloud2>("/aligned_points", 32);
submap_pub = nh.advertise<sensor_msgs::PointCloud2>("/radar_graph_slam/submap", 2);
}
private:
/**
* @brief initialize parameters
*/
void initialize_params() {
auto& pnh = private_nh;
points_topic = pnh.param<std::string>("points_topic", "/radar_enhanced_pcl");
use_ego_vel = pnh.param<bool>("use_ego_vel", false);
// The minimum tranlational distance and rotation angle between keyframes_.
// If this value is zero, frames are always compared with the previous frame
keyframe_delta_trans = pnh.param<double>("keyframe_delta_trans", 0.25);
keyframe_delta_angle = pnh.param<double>("keyframe_delta_angle", 0.15);
keyframe_delta_time = pnh.param<double>("keyframe_delta_time", 1.0);
// Registration validation by thresholding
enable_transform_thresholding = pnh.param<bool>("enable_transform_thresholding", false);
enable_imu_thresholding = pnh.param<bool>("enable_imu_thresholding", false);
max_acceptable_trans = pnh.param<double>("max_acceptable_trans", 1.0);
max_acceptable_angle = pnh.param<double>("max_acceptable_angle", 1.0);
max_diff_trans = pnh.param<double>("max_diff_trans", 1.0);
max_diff_angle = pnh.param<double>("max_diff_angle", 1.0);
max_egovel_cum = pnh.param<double>("max_egovel_cum", 1.0);
map_cloud_resolution = pnh.param<double>("map_cloud_resolution", 0.05);
keyframe_updater.reset(new KeyframeUpdater(pnh));
enable_scan_to_map = pnh.param<bool>("enable_scan_to_map", false);
max_submap_frames = pnh.param<int>("max_submap_frames", 5);
enable_imu_fusion = private_nh.param<bool>("enable_imu_fusion", false);
imu_debug_out = private_nh.param<bool>("imu_debug_out", false);
cout << "enable_imu_fusion = " << enable_imu_fusion << endl;
imu_fusion_ratio = private_nh.param<double>("imu_fusion_ratio", 0.1);
// graph_slam.reset(new GraphSLAM(pnh.param<std::string>("g2o_solver_type", "lm_var")));
// select a downsample method (VOXELGRID, APPROX_VOXELGRID, NONE)
std::string downsample_method = pnh.param<std::string>("downsample_method", "VOXELGRID");
double downsample_resolution = pnh.param<double>("downsample_resolution", 0.1);
if(downsample_method == "VOXELGRID") {
std::cout << "downsample: VOXELGRID " << downsample_resolution << std::endl;
auto voxelgrid = new pcl::VoxelGrid<PointT>();
voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter.reset(voxelgrid);
} else if(downsample_method == "APPROX_VOXELGRID") {
std::cout << "downsample: APPROX_VOXELGRID " << downsample_resolution << std::endl;
pcl::ApproximateVoxelGrid<PointT>::Ptr approx_voxelgrid(new pcl::ApproximateVoxelGrid<PointT>());
approx_voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter = approx_voxelgrid;
} else {
if(downsample_method != "NONE") {
std::cerr << "warning: unknown downsampling type (" << downsample_method << ")" << std::endl;
std::cerr << " : use passthrough filter" << std::endl;
}
std::cout << "downsample: NONE" << std::endl;
pcl::PassThrough<PointT>::Ptr passthrough(new pcl::PassThrough<PointT>());
downsample_filter = passthrough;
}
registration_s2s = select_registration_method(pnh);
registration_s2m = select_registration_method(pnh);
}
void imu_callback(const sensor_msgs::ImuConstPtr& imu_msg) {
Eigen::Quaterniond imu_quat_from(imu_msg->orientation.w, imu_msg->orientation.x, imu_msg->orientation.y, imu_msg->orientation.z);
Eigen::Quaterniond imu_quat_deskew = imu_quat_from * extQRPY;
imu_quat_deskew.normalize();
double roll, pitch, yaw;
// tf::quaternionMsgToTF(imu_odom_msg->orientation, orientation);
tf::Quaternion orientation = tf::Quaternion(imu_quat_deskew.x(),imu_quat_deskew.y(),imu_quat_deskew.z(),imu_quat_deskew.w());
tf::Matrix3x3(orientation).getRPY(roll, pitch, yaw);
imuPointerLast = (imuPointerLast + 1) % imuQueLength;
imuTime[imuPointerLast] = imu_msg->header.stamp.toSec();
imuRoll[imuPointerLast] = roll;
imuPitch[imuPointerLast] = pitch;
// cout << "get imu rp: " << roll << " " << pitch << endl;
sensor_msgs::ImuPtr imu(new sensor_msgs::Imu);
imu->header = imu_msg->header;
imu->angular_velocity = imu_msg->angular_velocity; imu->linear_acceleration = imu_msg->linear_acceleration;
imu->angular_velocity_covariance = imu_msg->angular_velocity_covariance;
imu->linear_acceleration_covariance, imu_msg->linear_acceleration_covariance;
imu->orientation_covariance = imu_msg->orientation_covariance;
imu->orientation.w=imu_quat_deskew.w(); imu->orientation.x = imu_quat_deskew.x(); imu->orientation.y = imu_quat_deskew.y(); imu->orientation.z = imu_quat_deskew.z();
{
std::lock_guard<std::mutex> lock(imu_queue_mutex);
imu_queue.push_back(imu);
}
static int cnt = 0;
if(cnt == 0) {
geometry_msgs::Quaternion imuQuat = tf::createQuaternionMsgFromRollPitchYaw(roll, pitch, 0);
global_orient_matrix = Eigen::Quaterniond(imuQuat.w, imuQuat.x, imuQuat.y, imuQuat.z).toRotationMatrix();
ROS_INFO_STREAM("Initial IMU euler angles (RPY): "
<< RAD2DEG(roll) << ", " << RAD2DEG(pitch) << ", " << RAD2DEG(yaw));
cnt = 1;
}
}
bool flush_imu_queue() {
std::lock_guard<std::mutex> lock(imu_queue_mutex);
if(keyframes.empty() || imu_queue.empty()) {
return false;
}
bool updated = false;
auto imu_cursor = imu_queue.begin();
for(size_t i=0; i < keyframes.size(); i++) {
auto keyframe = keyframes.at(i);
if(keyframe->stamp < (*imu_cursor)->header.stamp) {
continue;
}
if(keyframe->stamp > imu_queue.back()->header.stamp) {
break;
}
// find the imu data which is closest to the keyframe_
auto closest_imu = imu_cursor;
for(auto imu = imu_cursor; imu != imu_queue.end(); imu++) {
auto dt = ((*closest_imu)->header.stamp - keyframe->stamp).toSec();
auto dt2 = ((*imu)->header.stamp - keyframe->stamp).toSec();
if(std::abs(dt) < std::abs(dt2)) {
break;
}
closest_imu = imu;
}
// if the time residual between the imu and keyframe_ is too large, skip it
imu_cursor = closest_imu;
if(0.2 < std::abs(((*closest_imu)->header.stamp - keyframe->stamp).toSec())) {
continue;
}
sensor_msgs::Imu imu_;
imu_.header = (*closest_imu)->header; imu_.orientation = (*closest_imu)->orientation;
imu_.angular_velocity = (*closest_imu)->angular_velocity; imu_.linear_acceleration = (*closest_imu)->linear_acceleration;
imu_.angular_velocity_covariance = (*closest_imu)->angular_velocity_covariance;
imu_.linear_acceleration_covariance = (*closest_imu)->linear_acceleration_covariance;
imu_.orientation_covariance = (*closest_imu)->orientation_covariance;
keyframe->imu = imu_;
updated = true;
}
auto remove_loc = std::upper_bound(imu_queue.begin(), imu_queue.end(), keyframes.back()->stamp, [=](const ros::Time& stamp, const sensor_msgs::ImuConstPtr& imupoint) { return stamp < imupoint->header.stamp; });
imu_queue.erase(imu_queue.begin(), remove_loc);
return updated;
}
std::pair<bool, sensor_msgs::Imu> get_closest_imu(ros::Time frame_stamp) {
sensor_msgs::Imu imu_;
std::pair<bool, sensor_msgs::Imu> false_result {false, imu_};
if(keyframes.empty() || imu_queue.empty())
return false_result;
bool updated = false;
auto imu_cursor = imu_queue.begin();
// find the imu data which is closest to the keyframe_
auto closest_imu = imu_cursor;
for(auto imu = imu_cursor; imu != imu_queue.end(); imu++) {
auto dt = ((*closest_imu)->header.stamp - frame_stamp).toSec();
auto dt2 = ((*imu)->header.stamp - frame_stamp).toSec();
if(std::abs(dt) < std::abs(dt2)) {
break;
}
closest_imu = imu;
}
// if the time residual between the imu and keyframe_ is too large, skip it
imu_cursor = closest_imu;
if(0.2 < std::abs(((*closest_imu)->header.stamp - frame_stamp).toSec()))
return false_result;
imu_.header = (*closest_imu)->header; imu_.orientation = (*closest_imu)->orientation;
imu_.angular_velocity = (*closest_imu)->angular_velocity; imu_.linear_acceleration = (*closest_imu)->linear_acceleration;
imu_.angular_velocity_covariance = (*closest_imu)->angular_velocity_covariance;
imu_.linear_acceleration_covariance = (*closest_imu)->linear_acceleration_covariance;
imu_.orientation_covariance = (*closest_imu)->orientation_covariance;
updated = true;
// cout << (*closest_imu)->orientation <<endl;
std::pair<bool, sensor_msgs::Imu> result {updated, imu_};
return result;
}
void transformUpdate(Eigen::Matrix4d& odom_to_update) // IMU
{
if (imuPointerLast >= 0)
{
// cout << " ";
float imuRollLast = 0, imuPitchLast = 0;
while (imuPointerFront != imuPointerLast) {
if (timeLaserOdometry + scanPeriod < imuTime[imuPointerFront]) {
break;
}
imuPointerFront = (imuPointerFront + 1) % imuQueLength;
}
cout << " ";
if (timeLaserOdometry + scanPeriod > imuTime[imuPointerFront]) {
imuRollLast = imuRoll[imuPointerFront];
imuPitchLast = imuPitch[imuPointerFront];
cout << " ";
}
else {
cout << " ";
int imuPointerBack = (imuPointerFront + imuQueLength - 1) % imuQueLength;
float ratioFront = (timeLaserOdometry + scanPeriod - imuTime[imuPointerBack])
/ (imuTime[imuPointerFront] - imuTime[imuPointerBack]);
float ratioBack = (imuTime[imuPointerFront] - timeLaserOdometry - scanPeriod)
/ (imuTime[imuPointerFront] - imuTime[imuPointerBack]);
imuRollLast = imuRoll[imuPointerFront] * ratioFront + imuRoll[imuPointerBack] * ratioBack;
imuPitchLast = imuPitch[imuPointerFront] * ratioFront + imuPitch[imuPointerBack] * ratioBack;
}
Eigen::Matrix3d matr = odom_to_update.block<3, 3>(0, 0);
// Eigen::Vector3d xyz = odom_to_update.block<3, 1>(0, 3);
Eigen::Vector3d ypr_odom = R2ypr(matr.block<3,3>(0,0));
geometry_msgs::Quaternion imuQuat = tf::createQuaternionMsgFromRollPitchYaw(imuRollLast, imuPitchLast, ypr_odom(0));
Eigen::Matrix3d imu_rot = Eigen::Matrix3d(Eigen::Quaterniond(imuQuat.w, imuQuat.x, imuQuat.y, imuQuat.z));
Eigen::Vector3d ypr_imu = R2ypr(imu_rot);
// IMU orientation transformed from world coordinate to map coordinate
Eigen::Matrix3d imu_rot_transed = global_orient_matrix.inverse() * imu_rot;
Eigen::Vector3d ypr_imu_trans = R2ypr(imu_rot_transed);
double& yaw_ = ypr_odom(0);
double pitch_fused = (1 - imu_fusion_ratio) * ypr_odom(1) + imu_fusion_ratio * ypr_imu_trans(1);
double roll_fused = (1 - imu_fusion_ratio) * ypr_odom(2) + imu_fusion_ratio * ypr_imu_trans(2);
geometry_msgs::Quaternion rosQuat = tf::createQuaternionMsgFromRollPitchYaw(roll_fused, pitch_fused, yaw_);
Eigen::Quaterniond quat_updated = Eigen::Quaterniond(rosQuat.w, rosQuat.x, rosQuat.y, rosQuat.z);
odom_to_update.block<3, 3>(0, 0) = quat_updated.toRotationMatrix();
if (imu_debug_out)
cout << "IMU rp: " << RAD2DEG(ypr_imu(2)) << " " << RAD2DEG(ypr_imu(1))
<< ". IMU transed rp: " << RAD2DEG(ypr_imu_trans(2)) << " " << RAD2DEG(ypr_imu_trans(1))
// << ". Odom rp: " << RAD2DEG(ypr_odom(2)) << " " << RAD2DEG(ypr_odom(1))
// << ". Updated rp: " << RAD2DEG(roll_fused) << " " << RAD2DEG(pitch_fused)
// << ". Roll Pitch increment: " << RAD2DEG(roll_fused - ypr_odom(2)) << " " << RAD2DEG(pitch_fused - ypr_odom(1))
<< endl;
}
}
/**
* @brief callback for point clouds
* @param cloud_msg point cloud msg
*/
void pointcloud_callback(const geometry_msgs::TwistWithCovarianceStampedConstPtr& twistMsg, const sensor_msgs::PointCloud2ConstPtr& cloud_msg) {
if(!ros::ok()) {
return;
}
timeLaserOdometry = cloud_msg->header.stamp.toSec();
double this_cloud_time = cloud_msg->header.stamp.toSec();
static double last_cloud_time = this_cloud_time;
double dt = this_cloud_time - last_cloud_time;
double egovel_cum_x = twistMsg->twist.twist.linear.x * dt;
double egovel_cum_y = twistMsg->twist.twist.linear.y * dt;
double egovel_cum_z = twistMsg->twist.twist.linear.z * dt;
// If too large, set 0
if (pow(egovel_cum_x,2)+pow(egovel_cum_y,2)+pow(egovel_cum_z,2) > pow(max_egovel_cum, 2));
else egovel_cum.block<3, 1>(0, 3) = Eigen::Vector3d(egovel_cum_x, egovel_cum_y, egovel_cum_z);
last_cloud_time = this_cloud_time;
pcl::PointCloud<PointT>::Ptr cloud(new pcl::PointCloud<PointT>());
pcl::fromROSMsg(*cloud_msg, *cloud);
// Matching
Eigen::Matrix4d pose = matching(cloud_msg->header.stamp, cloud);
geometry_msgs::TwistWithCovariance twist = twistMsg->twist;
// publish map to odom frame
publish_odometry(cloud_msg->header.stamp, mapFrame, odometryFrame, pose, twist);
// In offline estimation, point clouds will be supplied until the published time
std_msgs::HeaderPtr read_until(new std_msgs::Header());
read_until->frame_id = points_topic;
read_until->stamp = cloud_msg->header.stamp + ros::Duration(1, 0);
read_until_pub.publish(read_until);
read_until->frame_id = "/filtered_points";
read_until_pub.publish(read_until);
}
void msf_pose_callback(const geometry_msgs::PoseWithCovarianceStampedConstPtr& pose_msg, bool after_update) {
if(after_update) {
msf_pose_after_update = pose_msg;
} else {
msf_pose = pose_msg;
}
}
/**
* @brief downsample a point cloud
* @param cloud input cloud
* @return downsampled point cloud
*/
pcl::PointCloud<PointT>::ConstPtr downsample(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
if(!downsample_filter) {
return cloud;
}
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
downsample_filter->setInputCloud(cloud);
downsample_filter->filter(*filtered);
return filtered;
}
/**
* @brief estimate the relative pose between an input cloud and a keyframe_ cloud
* @param stamp the timestamp of the input cloud
* @param cloud the input cloud
* @return the relative pose between the input cloud and the keyframe_ cloud
*/
Eigen::Matrix4d matching(const ros::Time& stamp, const pcl::PointCloud<PointT>::ConstPtr& cloud) {
if(!keyframe_cloud_s2s) {
prev_time = ros::Time();
prev_trans_s2s.setIdentity();
keyframe_pose_s2s.setIdentity();
keyframe_stamp = stamp;
keyframe_cloud_s2s = cloud;//downsample(cloud);
registration_s2s->setInputTarget(keyframe_cloud_s2s); // Scan-to-scan
if (enable_scan_to_map){
prev_trans_s2m.setIdentity();
keyframe_pose_s2m.setIdentity();
keyframe_cloud_s2m = cloud;
registration_s2m->setInputTarget(keyframe_cloud_s2m);
}
return Eigen::Matrix4d::Identity();
}
// auto filtered = downsample(cloud);
auto filtered = cloud;
// Set Source Cloud
registration_s2s->setInputSource(filtered);
if (enable_scan_to_map)
registration_s2m->setInputSource(filtered);
std::string msf_source;
Eigen::Isometry3d msf_delta = Eigen::Isometry3d::Identity();
pcl::PointCloud<PointT>::Ptr aligned(new pcl::PointCloud<PointT>());
Eigen::Matrix4d odom_s2s_now;
Eigen::Matrix4d odom_s2m_now;
// ********** Matching **********
Eigen::Matrix4d guess;
if (use_ego_vel)
guess = prev_trans_s2s * egovel_cum * msf_delta.matrix();
else
guess = prev_trans_s2s * msf_delta.matrix();
chrono::steady_clock::time_point t1 = chrono::steady_clock::now();
registration_s2s->align(*aligned, guess.cast<float>());
chrono::steady_clock::time_point t2 = chrono::steady_clock::now();
double time_used = chrono::duration_cast<chrono::duration<double>>(t2 - t1).count();
s2s_matching_time.push_back(time_used);
publish_scan_matching_status(stamp, cloud->header.frame_id, aligned, msf_source, msf_delta);
// If not converged, use last transformation
if(!registration_s2s->hasConverged()) {
NODELET_INFO_STREAM("scan matching_ has not converged!!");
NODELET_INFO_STREAM("ignore this frame(" << stamp << ")");
if (enable_scan_to_map) return keyframe_pose_s2m * prev_trans_s2m;
else return keyframe_pose_s2s * prev_trans_s2s;
}
Eigen::Matrix4d trans_s2s = registration_s2s->getFinalTransformation().cast<double>();
odom_s2s_now = keyframe_pose_s2s * trans_s2s;
Eigen::Matrix4d trans_s2m;
if (enable_scan_to_map){
registration_s2m->align(*aligned, guess.cast<float>());
if(!registration_s2m->hasConverged()) {
NODELET_INFO_STREAM("scan matching_ has not converged!!");
NODELET_INFO_STREAM("ignore this frame(" << stamp << ")");
return keyframe_pose_s2m * prev_trans_s2m;
}
trans_s2m = registration_s2m->getFinalTransformation().cast<double>();
odom_s2m_now = keyframe_pose_s2m * trans_s2m;
}
// Add abnormal judgment, that is, if the difference between the two frames matching point cloud
// transition matrix is too large, it will be discarded
bool thresholded = false;
if(enable_transform_thresholding) {
Eigen::Matrix4d radar_delta;
if(enable_scan_to_map) radar_delta = prev_trans_s2m.inverse() * trans_s2m;
else radar_delta = prev_trans_s2s.inverse() * trans_s2s;
double dx_rd = radar_delta.block<3, 1>(0, 3).norm();
// double da_rd = std::acos(Eigen::Quaterniond(radar_delta.block<3, 3>(0, 0)).w())*180/M_PI;
Eigen::AngleAxisd rotation_vector;
rotation_vector.fromRotationMatrix(radar_delta.block<3, 3>(0, 0));
double da_rd = rotation_vector.angle();
Eigen::Matrix3d rot_rd = radar_delta.block<3, 3>(0, 0).cast<double>();
bool too_large_trans = dx_rd > max_acceptable_trans || da_rd > max_acceptable_angle;
double da, dx, delta_rot_imu = 0;
Eigen::Matrix3d matrix_rot; Eigen::Vector3d delta_trans_egovel;
if (enable_imu_thresholding) {
// Use IMU orientation to determine whether the matching result is good or not
sensor_msgs::Imu frame_imu;
Eigen::Matrix3d rot_imu = Eigen::Matrix3d::Identity();
auto result = get_closest_imu(stamp);
if (result.first) {
frame_imu = result.second;
Eigen::Quaterniond imu_quat(frame_imu.orientation.w, frame_imu.orientation.x, frame_imu.orientation.y, frame_imu.orientation.z);
Eigen::Quaterniond prev_imu_quat(last_frame_imu.orientation.w, last_frame_imu.orientation.x, last_frame_imu.orientation.y, last_frame_imu.orientation.z);
rot_imu = (prev_imu_quat.inverse() * imu_quat).toRotationMatrix();
Eigen::Vector3d eulerAngle_imu = rot_imu.eulerAngles(0,1,2); // roll pitch yaw
Eigen::Vector3d eulerAngle_rd = last_radar_delta.block<3,3>(0,0).eulerAngles(0,1,2);
Eigen::AngleAxisd rollAngle(Eigen::AngleAxisd(restrict_rad(eulerAngle_imu(0)),Eigen::Vector3d::UnitX()));
Eigen::AngleAxisd pitchAngle(Eigen::AngleAxisd(restrict_rad(eulerAngle_imu(1)),Eigen::Vector3d::UnitY()));
Eigen::AngleAxisd yawAngle(Eigen::AngleAxisd(restrict_rad(eulerAngle_rd(2)),Eigen::Vector3d::UnitZ()));
matrix_rot = yawAngle * pitchAngle * rollAngle;
da = fabs(std::acos(Eigen::Quaterniond(rot_rd.inverse() * rot_imu).w()))*180/M_PI;
delta_rot_imu = fabs(std::acos(Eigen::Quaterniond(rot_imu).w()))*180/M_PI;
last_frame_imu = frame_imu;
}
delta_trans_egovel = egovel_cum.block<3,1>(0,3).cast<double>();
Eigen::Vector3d delta_trans_radar = radar_delta.block<3,1>(0,3).cast<double>();
dx = (delta_trans_egovel - delta_trans_radar).norm();
if (dx > max_diff_trans || da > max_diff_angle || too_large_trans) {
Eigen::Matrix4d mat_est(Eigen::Matrix4d::Identity());
mat_est.block<3, 3>(0, 0) = matrix_rot;
mat_est.block<3, 1>(0, 3) = delta_trans_egovel;
if (too_large_trans) cout << "Too large transform! " << dx_rd << "[m] " << da_rd << "[deg] ";
cout << "Difference of Odom and IMU/EgoVel too large " << dx << "[m] " << da << "[deg] (" << stamp << ")" << endl;
prev_trans_s2s = prev_trans_s2s * mat_est;
thresholded = true;
if (enable_scan_to_map){
prev_trans_s2m = prev_trans_s2m * mat_est;
odom_s2m_now = keyframe_pose_s2m * prev_trans_s2m;
}
else odom_s2s_now = keyframe_pose_s2s * prev_trans_s2s;
}
}
else {
if (too_large_trans) {
cout << "Too large transform!! " << dx_rd << "[m] " << da_rd << "[degree]"<<
" Ignore this frame (" << stamp << ")" << endl;
prev_trans_s2s = trans_s2s;
thresholded = true;
if (enable_scan_to_map){
prev_trans_s2m = trans_s2m;
odom_s2m_now = keyframe_pose_s2m * prev_trans_s2m * radar_delta;
}
else odom_s2s_now = keyframe_pose_s2s * prev_trans_s2s * radar_delta;
}
}
last_radar_delta = radar_delta;
if(0){
cout << "radar trans:" << dx_rd << " m rot:" << da_rd << " degree. EgoVel " << delta_trans_egovel.norm() << " m. "
<< "IMU rot " << delta_rot_imu << " degree." << endl;
cout << "dx " << dx << " m. da " << da << " degree." << endl;
}
}
prev_time = stamp;
if (!thresholded) {
prev_trans_s2s = trans_s2s;
prev_trans_s2m = trans_s2m;
}
//********** Decided whether to accept the frame as a key frame or not **********
if(keyframe_updater->decide(Eigen::Isometry3d(odom_s2s_now), stamp)) {
// Loose Coupling the IMU roll & pitch
if (enable_imu_fusion){
if(enable_scan_to_map) transformUpdate(odom_s2m_now);
else transformUpdate(odom_s2s_now);
}
keyframe_cloud_s2s = filtered;
registration_s2s->setInputTarget(keyframe_cloud_s2s);
keyframe_pose_s2s = odom_s2s_now;
keyframe_stamp = stamp;
prev_time = stamp;
prev_trans_s2s.setIdentity();
double accum_d = keyframe_updater->get_accum_distance();
KeyFrame::Ptr keyframe(new KeyFrame(keyframe_index, stamp, Eigen::Isometry3d(odom_s2s_now.cast<double>()), accum_d, cloud));
keyframe_index ++;
keyframes.push_back(keyframe);
// record keyframe's imu
flush_imu_queue();
if (enable_scan_to_map){
pcl::PointCloud<PointT>::Ptr submap_cloud(new pcl::PointCloud<PointT>());
pcl::PointCloud<PointT>::ConstPtr submap_cloud_downsampled;
for(size_t i=std::max(0, (int)keyframes.size()-max_submap_frames); i < keyframes.size()-1; i++){
Eigen::Matrix4d rel_pose = keyframes.at(i)->odom_scan2scan.matrix().inverse() * keyframes.back()->odom_scan2scan.matrix();
pcl::PointCloud<PointT>::Ptr cloud_transformed(new pcl::PointCloud<PointT>());
pcl::transformPointCloud(*keyframes.at(i)->cloud, *cloud_transformed, rel_pose);
*submap_cloud += *cloud_transformed;
}
submap_cloud_downsampled = downsample(submap_cloud);
keyframe_cloud_s2m = submap_cloud_downsampled;
registration_s2m->setInputTarget(keyframe_cloud_s2m);
keyframes.back()->odom_scan2map = Eigen::Isometry3d(odom_s2m_now);
keyframe_pose_s2m = odom_s2m_now;
prev_trans_s2m.setIdentity();
}
}
if (aligned_points_pub.getNumSubscribers() > 0)
{
pcl::transformPointCloud (*cloud, *aligned, odom_s2s_now);
aligned->header.frame_id = odometryFrame;
aligned_points_pub.publish(*aligned);
}
if (enable_scan_to_map)
return odom_s2m_now;
else
return odom_s2s_now;
}
/**
* @brief publish odometry
* @param stamp timestamp
* @param pose odometry pose to be published
*/
void publish_odometry(const ros::Time& stamp, const std::string& father_frame_id, const std::string& child_frame_id, const Eigen::Matrix4d& pose_in, const geometry_msgs::TwistWithCovariance twist_in) {
// publish transform stamped for IMU integration
geometry_msgs::TransformStamped odom_trans = matrix2transform(stamp, pose_in, father_frame_id, child_frame_id); //"map"
trans_pub.publish(odom_trans);
// broadcast the transform over TF
map2odom_broadcaster.sendTransform(odom_trans);
// publish the transform
nav_msgs::Odometry odom;
odom.header.stamp = stamp;
odom.header.frame_id = father_frame_id; // frame: /odom
odom.child_frame_id = child_frame_id;
odom.pose.pose.position.x = pose_in(0, 3);
odom.pose.pose.position.y = pose_in(1, 3);
odom.pose.pose.position.z = pose_in(2, 3);
odom.pose.pose.orientation = odom_trans.transform.rotation;
odom.twist = twist_in;
odom_pub.publish(odom);
}
/**
* @brief publish scan matching_ status
*/
void publish_scan_matching_status(const ros::Time& stamp, const std::string& frame_id, pcl::PointCloud<pcl::PointXYZI>::ConstPtr aligned, const std::string& msf_source, const Eigen::Isometry3d& msf_delta) {
if(!status_pub.getNumSubscribers()) {
return;
}
ScanMatchingStatus status;
status.header.frame_id = frame_id;
status.header.stamp = stamp;
status.has_converged = registration_s2s->hasConverged();
status.matching_error = registration_s2s->getFitnessScore();
const double max_correspondence_dist = 0.5;
int num_inliers = 0;
std::vector<int> k_indices;
std::vector<float> k_sq_dists;
for(int i=0; i<aligned->size(); i++) {
const auto& pt = aligned->at(i);
registration_s2s->getSearchMethodTarget()->nearestKSearch(pt, 1, k_indices, k_sq_dists);
if(k_sq_dists[0] < max_correspondence_dist * max_correspondence_dist) {
num_inliers++;
}
}
status.inlier_fraction = static_cast<float>(num_inliers) / aligned->size();
status.relative_pose = isometry2pose(Eigen::Isometry3d(registration_s2s->getFinalTransformation().cast<double>()));
if(!msf_source.empty()) {
status.prediction_labels.resize(1);
status.prediction_labels[0].data = msf_source;
status.prediction_errors.resize(1);
Eigen::Isometry3d error = Eigen::Isometry3d(registration_s2s->getFinalTransformation().cast<double>()).inverse() * msf_delta;
status.prediction_errors[0] = isometry2pose(error.cast<double>());
}
status_pub.publish(status);
}
void command_callback(const std_msgs::String& str_msg) {
if (str_msg.data == "time") {
std::sort(s2s_matching_time.begin(), s2s_matching_time.end());
double median = s2s_matching_time.at(size_t(s2s_matching_time.size() / 2));
cout << "Scan Matching time cost (median): " << median << endl;
}
}
private:
// ROS topics
ros::NodeHandle nh;
ros::NodeHandle mt_nh;
ros::NodeHandle private_nh;
// ros::Subscriber points_sub;
ros::Subscriber msf_pose_sub;
ros::Subscriber msf_pose_after_update_sub;
ros::Subscriber imu_sub;
std::mutex imu_queue_mutex;
std::deque<sensor_msgs::ImuConstPtr> imu_queue;
sensor_msgs::Imu last_frame_imu;
bool enable_imu_fusion;
bool imu_debug_out;
Eigen::Matrix3d global_orient_matrix; // The rotation matrix with initial IMU roll & pitch measurement (yaw = 0)
double timeLaserOdometry = 0;
int imuPointerFront;
int imuPointerLast;
double imuTime[imuQueLength];
float imuRoll[imuQueLength];
float imuPitch[imuQueLength];
double imu_fusion_ratio;
std::unique_ptr<message_filters::Subscriber<geometry_msgs::TwistWithCovarianceStamped>> ego_vel_sub;
std::unique_ptr<message_filters::Subscriber<sensor_msgs::PointCloud2>> points_sub;
std::unique_ptr<message_filters::Synchronizer<ApproxSyncPolicy>> sync;
// Submap
ros::Publisher submap_pub;
std::unique_ptr<KeyframeUpdater> keyframe_updater;
std::vector<KeyFrame::Ptr> keyframes;
size_t keyframe_index = 0;
double map_cloud_resolution;
int max_submap_frames;
bool enable_scan_to_map;
// std::unique_ptr<GraphSLAM> graph_slam;
// std::unique_ptr<InformationMatrixCalculator> inf_calclator;
ros::Publisher odom_pub;
ros::Publisher trans_pub;
// ros::Publisher keyframe_trans_pub;
ros::Publisher aligned_points_pub;
ros::Publisher status_pub;
ros::Publisher read_until_pub;
tf::TransformListener tf_listener;
tf::TransformBroadcaster map2odom_broadcaster; // map => odom_frame
std::string points_topic;
// keyframe_ parameters
double keyframe_delta_trans; // minimum distance between keyframes_
double keyframe_delta_angle; //
double keyframe_delta_time; //
// registration validation by thresholding
bool enable_transform_thresholding; //
bool enable_imu_thresholding;
double max_acceptable_trans; //
double max_acceptable_angle;
double max_diff_trans;
double max_diff_angle;
double max_egovel_cum;
Eigen::Matrix4d last_radar_delta = Eigen::Matrix4d::Identity();
// odometry calculation
geometry_msgs::PoseWithCovarianceStampedConstPtr msf_pose;
geometry_msgs::PoseWithCovarianceStampedConstPtr msf_pose_after_update;
Eigen::Matrix4d egovel_cum = Eigen::Matrix4d::Identity();
bool use_ego_vel;
ros::Time prev_time;
Eigen::Matrix4d prev_trans_s2s; // previous relative transform from keyframe_
Eigen::Matrix4d keyframe_pose_s2s; // keyframe_ pose
Eigen::Matrix4d prev_trans_s2m;
Eigen::Matrix4d keyframe_pose_s2m; // keyframe_ pose
ros::Time keyframe_stamp; // keyframe_ time
pcl::PointCloud<PointT>::ConstPtr keyframe_cloud_s2s; // keyframe_ point cloud
pcl::PointCloud<PointT>::ConstPtr keyframe_cloud_s2m; // keyframe_ point cloud
// Registration
pcl::Filter<PointT>::Ptr downsample_filter;
pcl::Registration<PointT, PointT>::Ptr registration_s2s; // Scan-to-Scan Registration
pcl::Registration<PointT, PointT>::Ptr registration_s2m; // Scan-to-Submap Registration
// Time evaluation
std::vector<double> s2s_matching_time;
ros::Subscriber command_sub;
};
} // namespace radar_graph_slam
PLUGINLIB_EXPORT_CLASS(radar_graph_slam::ScanMatchingOdometryNodelet, nodelet::Nodelet)
================================================
FILE: cmake/FindG2O.cmake
================================================
# Find the header files
FIND_PATH(G2O_INCLUDE_DIR g2o/core/base_vertex.h
${G2O_ROOT}/include
$ENV{G2O_ROOT}/include
$ENV{G2O_ROOT}
/usr/local/include
/usr/include
/opt/local/include
/sw/local/include
/sw/include
/opt/ros/$ENV{ROS_DISTRO}/include
NO_DEFAULT_PATH
)
# Macro to unify finding both the debug and release versions of the
# libraries; this is adapted from the OpenSceneGraph FIND_LIBRARY
# macro.
MACRO(FIND_G2O_LIBRARY MYLIBRARY MYLIBRARYNAME)
FIND_LIBRARY("${MYLIBRARY}_DEBUG"
NAMES "g2o_${MYLIBRARYNAME}_d"
PATHS
${G2O_ROOT}/lib/Debug
${G2O_ROOT}/lib
$ENV{G2O_ROOT}/lib/Debug
$ENV{G2O_ROOT}/lib
/opt/ros/$ENV{ROS_DISTRO}/lib
NO_DEFAULT_PATH
)
FIND_LIBRARY("${MYLIBRARY}_DEBUG"
NAMES "g2o_${MYLIBRARYNAME}_d"
PATHS
~/Library/Frameworks
/Library/Frameworks
/usr/local/lib
/usr/local/lib64
/usr/lib
/usr/lib64
/opt/local/lib
/sw/local/lib
/sw/lib
)
FIND_LIBRARY(${MYLIBRARY}
NAMES "g2o_${MYLIBRARYNAME}"
PATHS
${G2O_ROOT}/lib/Release
${G2O_ROOT}/lib
$ENV{G2O_ROOT}/lib/Release
$ENV{G2O_ROOT}/lib
/opt/ros/$ENV{ROS_DISTRO}/lib
NO_DEFAULT_PATH
)
FIND_LIBRARY(${MYLIBRARY}
NAMES "g2o_${MYLIBRARYNAME}"
PATHS
~/Library/Frameworks
/Library/Frameworks
/usr/local/lib
/usr/local/lib64
/usr/lib
/usr/lib64
/opt/local/lib
/sw/local/lib
/sw/lib
)
IF(NOT ${MYLIBRARY}_DEBUG)
IF(MYLIBRARY)
SET(${MYLIBRARY}_DEBUG ${MYLIBRARY})
ENDIF(MYLIBRARY)
ENDIF( NOT ${MYLIBRARY}_DEBUG)
ENDMACRO(FIND_G2O_LIBRARY LIBRARY LIBRARYNAME)
# Find the core elements
FIND_G2O_LIBRARY(G2O_STUFF_LIBRARY stuff)
FIND_G2O_LIBRARY(G2O_CORE_LIBRARY core)
# Find the CLI library
FIND_G2O_LIBRARY(G2O_CLI_LIBRARY cli)
# Find the pluggable solvers
FIND_G2O_LIBRARY(G2O_SOLVER_CHOLMOD solver_cholmod)
FIND_G2O_LIBRARY(G2O_SOLVER_CSPARSE solver_csparse)
FIND_G2O_LIBRARY(G2O_SOLVER_CSPARSE_EXTENSION csparse_extension)
FIND_G2O_LIBRARY(G2O_SOLVER_DENSE solver_dense)
FIND_G2O_LIBRARY(G2O_SOLVER_PCG solver_pcg)
FIND_G2O_LIBRARY(G2O_SOLVER_SLAM2D_LINEAR solver_slam2d_linear)
FIND_G2O_LIBRARY(G2O_SOLVER_STRUCTURE_ONLY solver_structure_only)
FIND_G2O_LIBRARY(G2O_SOLVER_EIGEN solver_eigen)
# Find the predefined types
FIND_G2O_LIBRARY(G2O_TYPES_DATA types_data)
FIND_G2O_LIBRARY(G2O_TYPES_ICP types_icp)
FIND_G2O_LIBRARY(G2O_TYPES_SBA types_sba)
FIND_G2O_LIBRARY(G2O_TYPES_SCLAM2D types_sclam2d)
FIND_G2O_LIBRARY(G2O_TYPES_SIM3 types_sim3)
FIND_G2O_LIBRARY(G2O_TYPES_SLAM2D types_slam2d)
FIND_G2O_LIBRARY(G2O_TYPES_SLAM3D types_slam3d)
FIND_G2O_LIBRARY(G2O_TYPES_SLAM3D_ADDONS types_slam3d_addons)
# G2O solvers declared found if we found at least one solver
SET(G2O_SOLVERS_FOUND "NO")
IF(G2O_SOLVER_CHOLMOD OR G2O_SOLVER_CSPARSE OR G2O_SOLVER_DENSE OR G2O_SOLVER_PCG OR G2O_SOLVER_SLAM2D_LINEAR OR G2O_SOLVER_STRUCTURE_ONLY OR G2O_SOLVER_EIGEN)
SET(G2O_SOLVERS_FOUND "YES")
ENDIF(G2O_SOLVER_CHOLMOD OR G2O_SOLVER_CSPARSE OR G2O_SOLVER_DENSE OR G2O_SOLVER_PCG OR G2O_SOLVER_SLAM2D_LINEAR OR G2O_SOLVER_STRUCTURE_ONLY OR G2O_SOLVER_EIGEN)
# G2O itself declared found if we found the core libraries and at least one solver
SET(G2O_FOUND "NO")
IF(G2O_STUFF_LIBRARY AND G2O_CORE_LIBRARY AND G2O_INCLUDE_DIR AND G2O_SOLVERS_FOUND)
SET(G2O_FOUND "YES")
ENDIF(G2O_STUFF_LIBRARY AND G2O_CORE_LIBRARY AND G2O_INCLUDE_DIR AND G2O_SOLVERS_FOUND)
================================================
FILE: config/params.yaml
================================================
radar_slam:
# Topics
pointCloudTopic: "/radar_enhanced_pcl" # Point cloud data <!-- pc2_raw inlier_pc2 segmented -->
imuTopic: "/vectornav/imu" # IMU data
odomTopic: "/odom" # IMU pre-preintegration odometry, same frequency as IMU
gpsTopic: "/ublox/fix" # GPS odometry topic from navsat, see module_navsat.launch file
# Frames
lidarFrame: ""
baselinkFrame: "base_link"
odometryFrame: "odom"
mapFrame: "map"
# GPS Settings
# useGpsElevation: false # if GPS elevation is bad, set to "false"
# gpsCovThreshold: 2.0 # m^2, threshold for using GPS data
# poseCovThreshold: 25.0 # m^2, threshold for using GPS data
# Export settings
# savePCD: false #
# savePCDDirectory: "/Downloads/4DRadarSLAM/" #
# Sensor Settings
# downsampleRate: 1 # default: 1. Downsample your data if too many points. i.e., 16 = 64 / 4, 16 = 16 / 1
# lidarMinRange: 1.0 # default: 1.0, minimum lidar range to be used
# lidarMaxRange: 1000.0 # default: 1000.0, maximum lidar range to be used
# IMU Settings
imuAccNoise: 0.0022281160035059417 # 3.9939570888238808e-03
imuGyrNoise: 0.00011667951042710442 # 1.5636343949698187e-03
imuAccBiasN: 0.00011782392708033614 # 6.4356659353532566e-05
imuGyrBiasN: 2.616129872371749e-06 # 3.5640318696367613e-05
imuGravity: 9.80511
imuRPYWeight: 0.01
# Extrinsics (Lidar -> IMU)
# extrinsicTrans: [0, 0, 0]
extrinsicTrans: [-0.3176955976234, -0.13761019052125, 0.05898352725152]
# extrinsicRot: [1, 0, 0,
# 0, -1, 0,
# 0, 0, -1]
# extrinsicRPY: [1, 0, 0,
# 0, -1, 0,
# 0, 0, -1]
extrinsicRot: [0.999735807578, -0.0215215701795, -0.0081643477385,
-0.02148120581797, -0.9997581134183, 0.00502853428037,
-0.00826995351904, -0.0048509797951, -0.99995400578406]
extrinsicRPY: [0.999735807578, -0.0215215701795, -0.0081643477385,
-0.02148120581797, -0.9997581134183, 0.00502853428037,
-0.00826995351904, -0.0048509797951, -0.99995400578406]
# extrinsicRot: [1, 0, 0,
# 0, 1, 0,
# 0, 0, 1]
# extrinsicRPY: [1, 0, 0,
# 0, 1, 0,
# 0, 0, 1]
================================================
FILE: include/dbscan/DBSCAN_kdtree.h
================================================
#ifndef DBSCAN_KDTREE_H
#define DBSCAN_KDTREE_H
#include <pcl/point_types.h>
#include "DBSCAN_simple.h"
template <typename PointT>
class DBSCANKdtreeCluster: public DBSCANSimpleCluster<PointT> {
protected:
virtual int radiusSearch (
int index, double radius, std::vector<int> &k_indices,
std::vector<float> &k_sqr_distances) const
{
return this->search_method_->radiusSearch(index, radius, k_indices, k_sqr_distances);
}
}; // class DBSCANCluster
#endif // DBSCAN_KDTREE_H
================================================
FILE: include/dbscan/DBSCAN_precomp.h
================================================
#ifndef DBSCAN_PRECOMP_H
#define DBSCAN_PRECOMP_H
#include <pcl/point_types.h>
#include "DBSCAN_simple.h"
template <typename PointT>
class DBSCANPrecompCluster : public DBSCANSimpleCluster<PointT> {
public:
virtual void setInputCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud) {
this->input_cloud_ = cloud;
int size = this->input_cloud_->points.size();
adjoint_indexes_ = std::vector<std::vector<int>>(size, std::vector<int>());
distances_ = std::vector<std::vector<float>>(size, std::vector<float>());
precomp();
}
protected:
std::vector<std::vector<float>> distances_;
std::vector<std::vector<int>> adjoint_indexes_;
void precomp() {
int size = this->input_cloud_->points.size();
for (int i = 0; i < size; i++) {
adjoint_indexes_[i].push_back(i);
distances_[i].push_back(0.0);
}
double radius_square = this->eps_ * this->eps_;
for (int i = 0; i < size; i++) {
for (int j = i+1; j < size; j++) {
double distance_x = this->input_cloud_->points[i].x - this->input_cloud_->points[j].x;
double distance_y = this->input_cloud_->points[i].y - this->input_cloud_->points[j].y;
double distance_z = this->input_cloud_->points[i].z - this->input_cloud_->points[j].z;
double distance_square = distance_x * distance_x + distance_y * distance_y + distance_z * distance_z;
if (distance_square <= radius_square) {
adjoint_indexes_[i].push_back(j);
adjoint_indexes_[j].push_back(i);
double distance = std::sqrt(distance_square);
distances_[i].push_back(distance);
distances_[j].push_back(distance);
}
}
}
}
virtual int radiusSearch(
int index, double radius, std::vector<int> &k_indices,
std::vector<float> &k_sqr_distances) const
{
// radius = eps_
k_indices = adjoint_indexes_[index];
k_sqr_distances = distances_[index];
return k_indices.size();
}
}; // class DBSCANCluster
#endif // DBSCAN_PRECOMP_H
================================================
FILE: include/dbscan/DBSCAN_simple.h
================================================
#ifndef DBSCAN_H
#define DBSCAN_H
#include <pcl/point_types.h>
#define UN_PROCESSED 0
#define PROCESSING 1
#define PROCESSED 2
inline bool comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) {
return (a.indices.size () < b.indices.size ());
}
template <typename PointT>
class DBSCANSimpleCluster {
public:
typedef typename pcl::PointCloud<PointT>::Ptr PointCloudPtr;
typedef typename pcl::search::KdTree<PointT>::Ptr KdTreePtr;
virtual void setInputCloud(PointCloudPtr cloud) {
input_cloud_ = cloud;
}
void setSearchMethod(KdTreePtr tree) {
search_method_ = tree;
}
void extract(std::vector<pcl::PointIndices>& cluster_indices) {
std::vector<int> nn_indices;
std::vector<float> nn_distances;
std::vector<bool> is_noise(input_cloud_->points.size(), false);
std::vector<int> types(input_cloud_->points.size(), UN_PROCESSED);
for (int i = 0; i < input_cloud_->points.size(); i++) {
if (types[i] == PROCESSED) {
continue;
}
int nn_size = radiusSearch(i, eps_, nn_indices, nn_distances);
if (nn_size < minPts_) {
is_noise[i] = true;
continue;
}
std::vector<int> seed_queue;
seed_queue.push_back(i);
types[i] = PROCESSED;
for (int j = 0; j < nn_size; j++) {
if (nn_indices[j] != i) {
seed_queue.push_back(nn_indices[j]);
types[nn_indices[j]] = PROCESSING;
}
} // for every point near the chosen core point.
int sq_idx = 1;
while (sq_idx < seed_queue.size()) {
int cloud_index = seed_queue[sq_idx];
if (is_noise[cloud_index] || types[cloud_index] == PROCESSED) {
// seed_queue.push_back(cloud_index);
types[cloud_index] = PROCESSED;
sq_idx++;
continue; // no need to check neighbors.
}
nn_size = radiusSearch(cloud_index, eps_, nn_indices, nn_distances);
if (nn_size >= minPts_) {
for (int j = 0; j < nn_size; j++) {
if (types[nn_indices[j]] == UN_PROCESSED) {
seed_queue.push_back(nn_indices[j]);
types[nn_indices[j]] = PROCESSING;
}
}
}
types[cloud_index] = PROCESSED;
sq_idx++;
}
if (seed_queue.size() >= min_pts_per_cluster_ && seed_queue.size () <= max_pts_per_cluster_) {
pcl::PointIndices r;
r.indices.resize(seed_queue.size());
for (int j = 0; j < seed_queue.size(); ++j) {
r.indices[j] = seed_queue[j];
}
// These two lines should not be needed: (can anyone confirm?) -FF
std::sort (r.indices.begin (), r.indices.end ());
r.indices.erase (std::unique (r.indices.begin (), r.indices.end ()), r.indices.end ());
r.header = input_cloud_->header;
cluster_indices.push_back (r); // We could avoid a copy by working directly in the vector
}
} // for every point in input cloud
std::sort (cluster_indices.rbegin (), cluster_indices.rend (), comparePointClusters);
}
void setClusterTolerance(double tolerance) {
eps_ = tolerance;
}
void setMinClusterSize (int min_cluster_size) {
min_pts_per_cluster_ = min_cluster_size;
}
void setMaxClusterSize (int max_cluster_size) {
max_pts_per_cluster_ = max_cluster_size;
}
void setCorePointMinPts(int core_point_min_pts) {
minPts_ = core_point_min_pts;
}
protected:
PointCloudPtr input_cloud_;
double eps_ {0.0};
int minPts_ {1}; // not including the point itself.
int min_pts_per_cluster_ {1};
int max_pts_per_cluster_ {std::numeric_limits<int>::max()};
KdTreePtr search_method_;
virtual int radiusSearch(
int index, double radius, std::vector<int> &k_indices,
std::vector<float> &k_sqr_distances) const
{
k_indices.clear();
k_sqr_distances.clear();
k_indices.push_back(index);
k_sqr_distances.push_back(0);
int size = input_cloud_->points.size();
double radius_square = radius * radius;
for (int i = 0; i < size; i++) {
if (i == index) {
continue;
}
double distance_x = input_cloud_->points[i].x - input_cloud_->points[index].x;
double distance_y = input_cloud_->points[i].y - input_cloud_->points[index].y;
double distance_z = input_cloud_->points[i].z - input_cloud_->points[index].z;
double distance_square = distance_x * distance_x + distance_y * distance_y + distance_z * distance_z;
if (distance_square <= radius_square) {
k_indices.push_back(i);
k_sqr_distances.push_back(std::sqrt(distance_square));
}
}
return k_indices.size();
}
}; // class DBSCANCluster
#endif // DBSCAN_H
================================================
FILE: include/g2o/edge_plane_identity.hpp
================================================
// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef EDGE_PLANE_IDENTITY_HPP
#define EDGE_PLANE_IDENTITY_HPP
#include <Eigen/Dense>
#include <g2o/core/base_binary_edge.h>
#include <g2o/types/slam3d_addons/vertex_plane.h>
namespace g2o {
/**
* @brief A modified version of g2o::EdgePlane. This class takes care of flipped plane normals.
*
*/
class EdgePlaneIdentity : public BaseBinaryEdge<4, Eigen::Vector4d, VertexPlane, VertexPlane> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgePlaneIdentity() : BaseBinaryEdge<4, Eigen::Vector4d, VertexPlane, VertexPlane>() {
_information.setIdentity();
_error.setZero();
}
void computeError() {
const VertexPlane* v1 = static_cast<const VertexPlane*>(_vertices[0]);
const VertexPlane* v2 = static_cast<const VertexPlane*>(_vertices[1]);
Eigen::Vector4d p1 = v1->estimate().toVector();
Eigen::Vector4d p2 = v2->estimate().toVector();
if(p1.dot(p2) < 0.0) {
p2 = -p2;
}
_error = (p2 - p1) - _measurement;
}
virtual bool read(std::istream& is) override {
Eigen::Vector4d v;
for(int i = 0; i < 4; ++i) {
is >> v[i];
}
setMeasurement(v);
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) {
information()(j, i) = information()(i, j);
}
}
}
return true;
}
virtual bool write(std::ostream& os) const override {
for(int i = 0; i < 4; ++i) {
os << _measurement[i] << " ";
}
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
os << " " << information()(i, j);
};
}
return os.good();
}
virtual void setMeasurement(const Eigen::Vector4d& m) override {
_measurement = m;
}
virtual int measurementDimension() const override {
return 4;
}
};
} // namespace g2o
#endif // EDGE_PLANE_PARALLEL_HPP
================================================
FILE: include/g2o/edge_plane_parallel.hpp
================================================
// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef EDGE_PLANE_PARALLEL_HPP
#define EDGE_PLANE_PARALLEL_HPP
#include <Eigen/Dense>
#include <g2o/core/base_binary_edge.h>
#include <g2o/types/slam3d_addons/vertex_plane.h>
namespace g2o {
class EdgePlaneParallel : public BaseBinaryEdge<3, Eigen::Vector3d, VertexPlane, VertexPlane> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgePlaneParallel() : BaseBinaryEdge<3, Eigen::Vector3d, VertexPlane, VertexPlane>() {
_information.setIdentity();
_error.setZero();
}
void computeError() override {
const VertexPlane* v1 = static_cast<const VertexPlane*>(_vertices[0]);
const VertexPlane* v2 = static_cast<const VertexPlane*>(_vertices[1]);
Eigen::Vector3d normal1 = v1->estimate().normal();
Eigen::Vector3d normal2 = v2->estimate().normal();
if(normal1.dot(normal2) < 0.0) {
normal2 = -normal2;
}
_error = (normal2 - normal1) - _measurement;
}
virtual bool read(std::istream& is) override {
Eigen::Vector3d v;
for(int i = 0; i < 3; ++i) {
is >> v[i];
}
setMeasurement(v);
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) {
information()(j, i) = information()(i, j);
}
}
}
return true;
}
virtual bool write(std::ostream& os) const override {
for(int i = 0; i < 3; ++i) {
os << _measurement[i] << " ";
}
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
os << " " << information()(i, j);
};
}
return os.good();
}
virtual void setMeasurement(const Eigen::Vector3d& m) override {
_measurement = m;
}
virtual int measurementDimension() const override {
return 3;
}
};
class EdgePlanePerpendicular : public BaseBinaryEdge<1, Eigen::Vector3d, VertexPlane, VertexPlane> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgePlanePerpendicular() : BaseBinaryEdge<1, Eigen::Vector3d, VertexPlane, VertexPlane>() {
_information.setIdentity();
_error.setZero();
}
void computeError() override {
const VertexPlane* v1 = static_cast<const VertexPlane*>(_vertices[0]);
const VertexPlane* v2 = static_cast<const VertexPlane*>(_vertices[1]);
Eigen::Vector3d normal1 = v1->estimate().normal().normalized();
Eigen::Vector3d normal2 = v2->estimate().normal().normalized();
_error[0] = normal1.dot(normal2);
}
virtual bool read(std::istream& is) override {
Eigen::Vector3d v;
for(int i = 0; i < 3; ++i) {
is >> v[i];
}
setMeasurement(v);
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) {
information()(j, i) = information()(i, j);
}
}
}
return true;
}
virtual bool write(std::ostream& os) const override {
for(int i = 0; i < 3; ++i) {
os << _measurement[i] << " ";
}
for(int i = 0; i < information().rows(); ++i) {
for(int j = i; j < information().cols(); ++j) {
os << " " << information()(i, j);
};
}
return os.good();
}
virtual void setMeasurement(const Eigen::Vector3d& m) override {
_measurement = m;
}
virtual int measurementDimension() const override {
return 3;
}
};
} // namespace g2o
#endif // EDGE_PLANE_PARALLEL_HPP
================================================
FILE: include/g2o/edge_plane_prior.hpp
================================================
// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef EDGE_PLANE_PRIOR_HPP
#define EDGE_PLANE_PRIOR_HPP
#include <Eigen/Dense>
#include <g2o/core/base_unary_edge.h>
#include <g2o/types/slam3d_addons/vertex_plane.h>
namespace g2o {
class EdgePlanePriorNormal : public g2o::BaseUnaryEdge<3, Eigen::Vector3d, g2o::VertexPlane> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgePlanePriorNormal() : g2o::BaseUnaryEdge<3, Eigen::Vector3d, g2o::VertexPlane>() {}
void computeError() override {
const g2o::VertexPlane* v1 = static_cast<const g2o::VertexPlane*>(_vertices[0]);
Eigen::Vector3d normal = v1->estimate().normal();
if(normal.dot(_measurement) < 0.0) {
normal = -normal;
}
_error = normal - _measurement;
}
void setMeasurement(const Eigen::Vector3d& m) override {
_measurement = m;
}
virtual bool read(std::istream& is) override {
Eigen::Vector3d v;
is >> v(0) >> v(1) >> v(2);
setMeasurement(v);
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) information()(j, i) = information()(i, j);
}
return true;
}
virtual bool write(std::ostream& os) const override {
Eigen::Vector3d v = _measurement;
os << v(0) << " " << v(1) << " " << v(2) << " ";
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) os << " " << information()(i, j);
return os.good();
}
};
class EdgePlanePriorDistance : public g2o::BaseUnaryEdge<1, double, g2o::VertexPlane> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgePlanePriorDistance() : g2o::BaseUnaryEdge<1, double, g2o::VertexPlane>() {}
void computeError() override {
const g2o::VertexPlane* v1 = static_cast<const g2o::VertexPlane*>(_vertices[0]);
_error[0] = _measurement - v1->estimate().distance();
}
void setMeasurement(const double& m) override {
_measurement = m;
}
virtual bool read(std::istream& is) override {
is >> _measurement;
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) information()(j, i) = information()(i, j);
}
return true;
}
virtual bool write(std::ostream& os) const override {
os << _measurement;
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) os << " " << information()(i, j);
return os.good();
}
};
} // namespace g2o
#endif // EDGE_SE3_PRIORXY_HPP
================================================
FILE: include/g2o/edge_se3_gt_utm.hpp
================================================
// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef KKL_G2O_EDGE_SE3_GTUTM_HPP
#define KKL_G2O_EDGE_SE3_GTUTM_HPP
#include <g2o/types/slam3d/types_slam3d.h>
#include <g2o/types/slam3d_addons/types_slam3d_addons.h>
namespace g2o {
class EdgeSE3GtUTM : public g2o::BaseUnaryEdge<3, Eigen::Vector3d, g2o::VertexSE3> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgeSE3GtUTM() : g2o::BaseUnaryEdge<3, Eigen::Vector3d, g2o::VertexSE3>() {}
void computeError() override {
const g2o::VertexSE3* v1 = static_cast<const g2o::VertexSE3*>(_vertices[0]);
Eigen::Vector4d utm_homogeneous = Eigen::Vector4d(_measurement_utm(0), _measurement_utm(1), _measurement_utm(2), 1);
Eigen::Vector3d estimate = (v1->estimate() * utm_homogeneous).head(3);
_error = estimate - _measurement;
}
void setMeasurement(const Eigen::Vector3d& m) override {
_measurement = m;
}
void setMeasurement_utm(const Eigen::Vector3d& m){
_measurement_utm = m;
}
virtual bool read(std::istream& is) override {
Eigen::Vector3d v;
is >> v(0) >> v(1) >> v(2);
setMeasurement(v);
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) {
is >> information()(i, j);
if(i != j) information()(j, i) = information()(i, j);
}
return true;
}
virtual bool write(std::ostream& os) const override {
Eigen::Vector3d v = _measurement;
os << v(0) << " " << v(1) << " " << v(2) << " ";
for(int i = 0; i < information().rows(); ++i)
for(int j = i; j < information().cols(); ++j) os << " " << information()(i, j);
return os.good();
}
private:
Eigen::Vector3d _measurement_utm;
};
} // namespace g2o
#endif
================================================
FILE: include/g2o/edge_se3_plane.hpp
================================================
// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF
gitextract_sqtxga8a/
├── CMakeLists.txt
├── LICENSE
├── README.md
├── apps/
│ ├── preprocessing_nodelet.cpp
│ ├── radar_graph_slam_nodelet.cpp
│ └── scan_matching_odometry_nodelet.cpp
├── cmake/
│ └── FindG2O.cmake
├── config/
│ └── params.yaml
├── include/
│ ├── dbscan/
│ │ ├── DBSCAN_kdtree.h
│ │ ├── DBSCAN_precomp.h
│ │ └── DBSCAN_simple.h
│ ├── g2o/
│ │ ├── edge_plane_identity.hpp
│ │ ├── edge_plane_parallel.hpp
│ │ ├── edge_plane_prior.hpp
│ │ ├── edge_se3_gt_utm.hpp
│ │ ├── edge_se3_plane.hpp
│ │ ├── edge_se3_priorquat.hpp
│ │ ├── edge_se3_priorvec.hpp
│ │ ├── edge_se3_priorxy.hpp
│ │ ├── edge_se3_priorxyz.hpp
│ │ ├── edge_se3_priorz.hpp
│ │ ├── edge_se3_se3.hpp
│ │ ├── edge_se3_z.hpp
│ │ └── robust_kernel_io.hpp
│ ├── radar_ego_velocity_estimator.h
│ ├── radar_graph_slam/
│ │ ├── graph_slam.hpp
│ │ ├── information_matrix_calculator.hpp
│ │ ├── keyframe.hpp
│ │ ├── keyframe_updater.hpp
│ │ ├── loop_detector.hpp
│ │ ├── map_cloud_generator.hpp
│ │ ├── nmea_sentence_parser.hpp
│ │ ├── polynomial_interpolation.hpp
│ │ ├── registrations.hpp
│ │ ├── ros_time_hash.hpp
│ │ └── ros_utils.hpp
│ ├── rio_utils/
│ │ ├── data_types.h
│ │ ├── math_helper.h
│ │ ├── radar_point_cloud.h
│ │ ├── ros_helper.h
│ │ ├── simple_profiler.h
│ │ └── strapdown.h
│ ├── scan_context/
│ │ ├── KDTreeVectorOfVectorsAdaptor.h
│ │ ├── Scancontext.h
│ │ ├── nanoflann.hpp
│ │ └── tictoc.h
│ └── utility_radar.h
├── launch/
│ ├── radar_graph_slam.launch
│ ├── rosbag_play_radar_carpark1.launch
│ ├── rosbag_play_radar_carpark3.launch
│ ├── rosbag_play_radar_garden.launch
│ ├── rosbag_play_radar_nanyanglink.launch
│ ├── rosbag_play_radar_ntuloop1.launch
│ ├── rosbag_play_radar_ntuloop2.launch
│ ├── rosbag_play_radar_ntuloop3.launch
│ └── rosbag_play_radar_smoke.launch
├── msg/
│ ├── FloorCoeffs.msg
│ └── ScanMatchingStatus.msg
├── nodelet_plugins.xml
├── package.xml
├── rviz/
│ └── radar_graph_slam.rviz
├── setup.py
├── src/
│ ├── g2o/
│ │ └── robust_kernel_io.cpp
│ ├── gps_traj_align.cpp
│ ├── gt_adjust.cpp
│ ├── radar_ego_velocity_estimator.cpp
│ └── radar_graph_slam/
│ ├── Scancontext.cpp
│ ├── __init__.py
│ ├── bag_player.py
│ ├── ford2bag.py
│ ├── graph_slam.cpp
│ ├── information_matrix_calculator.cpp
│ ├── keyframe.cpp
│ ├── loop_detector.cpp
│ ├── map2odom_publisher.py
│ ├── map_cloud_generator.cpp
│ └── registrations.cpp
└── srv/
├── DumpGraph.srv
└── SaveMap.srv
SYMBOL INDEX (453 symbols across 55 files)
FILE: apps/preprocessing_nodelet.cpp
type radar_graph_slam (line 44) | namespace radar_graph_slam {
class PreprocessingNodelet (line 46) | class PreprocessingNodelet : public nodelet::Nodelet, public ParamServ...
method PreprocessingNodelet (line 51) | PreprocessingNodelet() {}
method onInit (line 54) | virtual void onInit() {
method initializeTransformation (line 82) | void initializeTransformation(){
method initializeParams (line 107) | void initializeParams() {
method imu_callback (line 208) | void imu_callback(const sensor_msgs::ImuConstPtr& imu_msg) {
method cloud_callback (line 267) | void cloud_callback(const sensor_msgs::PointCloud::ConstPtr& eagle_...
method passthrough (line 392) | pcl::PointCloud<PointT>::ConstPtr passthrough(const pcl::PointCloud<...
method downsample (line 408) | pcl::PointCloud<PointT>::ConstPtr downsample(const pcl::PointCloud<P...
method outlier_removal (line 426) | pcl::PointCloud<PointT>::ConstPtr outlier_removal(const pcl::PointCl...
method distance_filter (line 439) | pcl::PointCloud<PointT>::ConstPtr distance_filter(const pcl::PointCl...
method deskewing (line 465) | pcl::PointCloud<PointT>::ConstPtr deskewing(const pcl::PointCloud<Po...
method RadarRaw2PointCloudXYZ (line 528) | bool RadarRaw2PointCloudXYZ(const pcl::PointCloud<RadarPointCloudTyp...
method RadarRaw2PointCloudXYZI (line 540) | bool RadarRaw2PointCloudXYZI(const pcl::PointCloud<RadarPointCloudTy...
method command_callback (line 554) | void command_callback(const std_msgs::String& str_msg) {
FILE: apps/radar_graph_slam_nodelet.cpp
type radar_graph_slam (line 77) | namespace radar_graph_slam {
class RadarGraphSlamNodelet (line 79) | class RadarGraphSlamNodelet : public nodelet::Nodelet, public ParamSer...
method RadarGraphSlamNodelet (line 85) | RadarGraphSlamNodelet() {}
method onInit (line 88) | virtual void onInit() {
method cloud_callback (line 196) | void cloud_callback(const nav_msgs::OdometryConstPtr& odom_msg, cons...
method imu_callback (line 293) | void imu_callback(const sensor_msgs::ImuConstPtr& imu_odom_msg) {
method imu_odom_callback (line 328) | void imu_odom_callback(const nav_msgs::OdometryConstPtr& imu_odom_ms...
method preIntegrationTransform (line 335) | geometry_msgs::Transform preIntegrationTransform(){
method barometer_callback (line 441) | void barometer_callback(const barometer_bmp388::BarometerPtr& baro_m...
method flush_barometer_queue (line 449) | bool flush_barometer_queue() {
method flush_keyframe_queue (line 523) | bool flush_keyframe_queue() {
method optimization_timer_callback (line 614) | void optimization_timer_callback(const ros::WallTimerEvent& event) {
method addLoopFactor (line 700) | void addLoopFactor()
method map_points_publish_timer_callback (line 722) | void map_points_publish_timer_callback(const ros::WallTimerEvent& ev...
method create_marker_array (line 749) | visualization_msgs::MarkerArray create_marker_array(const ros::Time&...
method dump_service (line 990) | bool dump_service(radar_graph_slam::DumpGraphRequest& req, radar_gra...
method save_map_service (line 1038) | bool save_map_service(radar_graph_slam::SaveMapRequest& req, radar_g...
method nmea_callback (line 1071) | void nmea_callback(const nmea_msgs::SentenceConstPtr& nmea_msg) {
method navsat_callback (line 1083) | void navsat_callback(const sensor_msgs::NavSatFixConstPtr& navsat_ms...
method gps_callback (line 1099) | void gps_callback(const geographic_msgs::GeoPointStampedPtr& gps_msg) {
method flush_gps_queue (line 1109) | bool flush_gps_queue() {
method command_callback (line 1190) | void command_callback(const std_msgs::String& str_msg) {
FILE: apps/scan_matching_odometry_nodelet.cpp
type radar_graph_slam (line 61) | namespace radar_graph_slam {
class ScanMatchingOdometryNodelet (line 63) | class ScanMatchingOdometryNodelet : public nodelet::Nodelet, public Pa...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 68) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method onInit (line 73) | virtual void onInit() {
method initialize_params (line 108) | void initialize_params() {
method imu_callback (line 167) | void imu_callback(const sensor_msgs::ImuConstPtr& imu_msg) {
method flush_imu_queue (line 206) | bool flush_imu_queue() {
method get_closest_imu (line 251) | std::pair<bool, sensor_msgs::Imu> get_closest_imu(ros::Time frame_st...
method transformUpdate (line 287) | void transformUpdate(Eigen::Matrix4d& odom_to_update) // IMU
method pointcloud_callback (line 347) | void pointcloud_callback(const geometry_msgs::TwistWithCovarianceSta...
method msf_pose_callback (line 385) | void msf_pose_callback(const geometry_msgs::PoseWithCovarianceStampe...
method downsample (line 398) | pcl::PointCloud<PointT>::ConstPtr downsample(const pcl::PointCloud<P...
method matching (line 416) | Eigen::Matrix4d matching(const ros::Time& stamp, const pcl::PointClo...
method publish_odometry (line 627) | void publish_odometry(const ros::Time& stamp, const std::string& fat...
method publish_scan_matching_status (line 653) | void publish_scan_matching_status(const ros::Time& stamp, const std:...
method command_callback (line 692) | void command_callback(const std_msgs::String& str_msg) {
FILE: include/dbscan/DBSCAN_precomp.h
function precomp (line 22) | void precomp() {
function virtual (line 46) | virtual int radiusSearch(
FILE: include/dbscan/DBSCAN_simple.h
function comparePointClusters (line 10) | inline bool comparePointClusters (const pcl::PointIndices &a, const pcl:...
type typename (line 18) | typedef typename pcl::search::KdTree<PointT>::Ptr KdTreePtr;
function virtual (line 19) | virtual void setInputCloud(PointCloudPtr cloud) {
function setSearchMethod (line 23) | void setSearchMethod(KdTreePtr tree) {
function extract (line 27) | void extract(std::vector<pcl::PointIndices>& cluster_indices) {
function setClusterTolerance (line 92) | void setClusterTolerance(double tolerance) {
function setMinClusterSize (line 96) | void setMinClusterSize (int min_cluster_size) {
function setMaxClusterSize (line 100) | void setMaxClusterSize (int max_cluster_size) {
function setCorePointMinPts (line 104) | void setCorePointMinPts(int core_point_min_pts) {
function minPts_ (line 112) | int minPts_ {1}
function min_pts_per_cluster_ (line 113) | int min_pts_per_cluster_ {1}
function max_pts_per_cluster_ (line 114) | int max_pts_per_cluster_ {std::numeric_limits<int>::max()};
FILE: include/g2o/edge_plane_identity.hpp
type g2o (line 34) | namespace g2o {
class EdgePlaneIdentity (line 40) | class EdgePlaneIdentity : public BaseBinaryEdge<4, Eigen::Vector4d, Ve...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 42) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 47) | void computeError() {
method read (line 60) | virtual bool read(std::istream& is) override {
method write (line 79) | virtual bool write(std::ostream& os) const override {
method setMeasurement (line 92) | virtual void setMeasurement(const Eigen::Vector4d& m) override {
method measurementDimension (line 96) | virtual int measurementDimension() const override {
FILE: include/g2o/edge_plane_parallel.hpp
type g2o (line 34) | namespace g2o {
class EdgePlaneParallel (line 36) | class EdgePlaneParallel : public BaseBinaryEdge<3, Eigen::Vector3d, Ve...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 38) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 44) | void computeError() override {
method read (line 57) | virtual bool read(std::istream& is) override {
method write (line 76) | virtual bool write(std::ostream& os) const override {
method setMeasurement (line 89) | virtual void setMeasurement(const Eigen::Vector3d& m) override {
method measurementDimension (line 93) | virtual int measurementDimension() const override {
class EdgePlanePerpendicular (line 98) | class EdgePlanePerpendicular : public BaseBinaryEdge<1, Eigen::Vector3...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 100) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 106) | void computeError() override {
method read (line 116) | virtual bool read(std::istream& is) override {
method write (line 135) | virtual bool write(std::ostream& os) const override {
method setMeasurement (line 148) | virtual void setMeasurement(const Eigen::Vector3d& m) override {
method measurementDimension (line 152) | virtual int measurementDimension() const override {
FILE: include/g2o/edge_plane_prior.hpp
type g2o (line 34) | namespace g2o {
class EdgePlanePriorNormal (line 35) | class EdgePlanePriorNormal : public g2o::BaseUnaryEdge<3, Eigen::Vecto...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 37) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 40) | void computeError() override {
method setMeasurement (line 51) | void setMeasurement(const Eigen::Vector3d& m) override {
method read (line 55) | virtual bool read(std::istream& is) override {
method write (line 66) | virtual bool write(std::ostream& os) const override {
class EdgePlanePriorDistance (line 75) | class EdgePlanePriorDistance : public g2o::BaseUnaryEdge<1, double, g2...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 77) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 80) | void computeError() override {
method setMeasurement (line 85) | void setMeasurement(const double& m) override {
method read (line 89) | virtual bool read(std::istream& is) override {
method write (line 98) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_gt_utm.hpp
type g2o (line 33) | namespace g2o {
class EdgeSE3GtUTM (line 34) | class EdgeSE3GtUTM : public g2o::BaseUnaryEdge<3, Eigen::Vector3d, g2o...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 36) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 39) | void computeError() override {
method setMeasurement (line 47) | void setMeasurement(const Eigen::Vector3d& m) override {
method setMeasurement_utm (line 51) | void setMeasurement_utm(const Eigen::Vector3d& m){
method read (line 55) | virtual bool read(std::istream& is) override {
method write (line 66) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_plane.hpp
type g2o (line 34) | namespace g2o {
class EdgeSE3Plane (line 35) | class EdgeSE3Plane : public g2o::BaseBinaryEdge<3, g2o::Plane3D, g2o::...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 37) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 40) | void computeError() override {
method setMeasurement (line 49) | void setMeasurement(const g2o::Plane3D& m) override {
method read (line 53) | virtual bool read(std::istream& is) override {
method write (line 64) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_priorquat.hpp
type g2o (line 33) | namespace g2o {
class EdgeSE3PriorQuat (line 34) | class EdgeSE3PriorQuat : public g2o::BaseUnaryEdge<3, Eigen::Quaternio...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 36) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 39) | void computeError() override {
method setMeasurement (line 50) | void setMeasurement(const Eigen::Quaterniond& m) override {
method read (line 57) | virtual bool read(std::istream& is) override {
method write (line 68) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_priorvec.hpp
type g2o (line 33) | namespace g2o {
class EdgeSE3PriorVec (line 34) | class EdgeSE3PriorVec : public g2o::BaseUnaryEdge<3, Eigen::Matrix<dou...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 36) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 39) | void computeError() override {
method setMeasurement (line 50) | void setMeasurement(const Eigen::Matrix<double, 6, 1>& m) override {
method read (line 55) | virtual bool read(std::istream& is) override {
method write (line 66) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_priorxy.hpp
type g2o (line 33) | namespace g2o {
class EdgeSE3PriorXY (line 34) | class EdgeSE3PriorXY : public g2o::BaseUnaryEdge<2, Eigen::Vector2d, g...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 36) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 39) | void computeError() override {
method setMeasurement (line 46) | void setMeasurement(const Eigen::Vector2d& m) override {
method read (line 50) | virtual bool read(std::istream& is) override {
method write (line 61) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_priorxyz.hpp
type g2o (line 33) | namespace g2o {
class EdgeSE3PriorXYZ (line 34) | class EdgeSE3PriorXYZ : public g2o::BaseUnaryEdge<3, Eigen::Vector3d, ...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 36) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 39) | void computeError() override {
method setMeasurement (line 46) | void setMeasurement(const Eigen::Vector3d& m) override {
method read (line 50) | virtual bool read(std::istream& is) override {
method write (line 61) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_priorz.hpp
type Eigen (line 33) | namespace Eigen {
type g2o (line 37) | namespace g2o {
class EdgeSE3PriorZ (line 38) | class EdgeSE3PriorZ : public g2o::BaseUnaryEdge<1, Eigen::Vector1d, g2...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 41) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 44) | void computeError() override {
method setMeasurement (line 51) | void setMeasurement(const Eigen::Vector1d& m) override {
method read (line 55) | virtual bool read(std::istream& is) override {
method write (line 66) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_se3.hpp
type g2o (line 38) | namespace g2o {
class EdgeSE3SE3 (line 39) | class EdgeSE3SE3 : public g2o::BaseBinaryEdge<6, g2o::SE3Quat, g2o::Ve...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 41) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 44) | void computeError() override {
method setMeasurement (line 87) | void setMeasurement(const g2o::SE3Quat& m) override {
method read (line 91) | virtual bool read(std::istream& is) override {
method write (line 104) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/edge_se3_z.hpp
type Eigen (line 33) | namespace Eigen {
type g2o (line 37) | namespace g2o {
class EdgeSE3Z (line 38) | class EdgeSE3Z : public g2o::BaseBinaryEdge<1, Eigen::Vector1d, g2o::V...
method EIGEN_MAKE_ALIGNED_OPERATOR_NEW (line 41) | EIGEN_MAKE_ALIGNED_OPERATOR_NEW
method computeError (line 44) | void computeError() override {
method setMeasurement (line 52) | void setMeasurement(const Eigen::Vector1d& m) override {
method read (line 56) | virtual bool read(std::istream& is) override {
method write (line 67) | virtual bool write(std::ostream& os) const override {
FILE: include/g2o/robust_kernel_io.hpp
type g2o (line 9) | namespace g2o {
FILE: include/radar_ego_velocity_estimator.h
function namespace (line 27) | namespace rio
FILE: include/radar_graph_slam/graph_slam.hpp
type g2o (line 16) | namespace g2o {
class VertexSE3 (line 17) | class VertexSE3
class VertexPlane (line 18) | class VertexPlane
class VertexPointXYZ (line 19) | class VertexPointXYZ
class EdgeSE3 (line 20) | class EdgeSE3
class EdgeSE3Plane (line 21) | class EdgeSE3Plane
class EdgeSE3PointXYZ (line 22) | class EdgeSE3PointXYZ
class EdgeSE3PriorXY (line 23) | class EdgeSE3PriorXY
class EdgeSE3PriorXYZ (line 24) | class EdgeSE3PriorXYZ
class EdgeSE3PriorVec (line 25) | class EdgeSE3PriorVec
class EdgeSE3PriorQuat (line 26) | class EdgeSE3PriorQuat
class EdgePlane (line 27) | class EdgePlane
class EdgePlaneIdentity (line 28) | class EdgePlaneIdentity
class EdgePlaneParallel (line 29) | class EdgePlaneParallel
class EdgePlanePerpendicular (line 30) | class EdgePlanePerpendicular
class EdgePlanePriorNormal (line 31) | class EdgePlanePriorNormal
class EdgePlanePriorDistance (line 32) | class EdgePlanePriorDistance
class RobustKernelFactory (line 33) | class RobustKernelFactory
type radar_graph_slam (line 36) | namespace radar_graph_slam {
class GraphSLAM (line 38) | class GraphSLAM {
FILE: include/radar_graph_slam/information_matrix_calculator.hpp
type radar_graph_slam (line 10) | namespace radar_graph_slam {
class InformationMatrixCalculator (line 12) | class InformationMatrixCalculator {
method InformationMatrixCalculator (line 16) | InformationMatrixCalculator() {}
method load (line 21) | void load(ParamServer& params) {
method weight (line 39) | double weight(double a, double max_x, double min_y, double max_y, do...
FILE: include/radar_graph_slam/keyframe.hpp
type g2o (line 16) | namespace g2o {
class VertexSE3 (line 17) | class VertexSE3
class HyperGraph (line 18) | class HyperGraph
class SparseOptimizer (line 19) | class SparseOptimizer
type radar_graph_slam (line 22) | namespace radar_graph_slam {
type KeyFrame (line 27) | struct KeyFrame {
type KeyFrameSnapshot (line 67) | struct KeyFrameSnapshot {
FILE: include/radar_graph_slam/keyframe_updater.hpp
type radar_graph_slam (line 11) | namespace radar_graph_slam {
function decide (line 16) | class KeyframeUpdater {
function get_accum_distance (line 69) | double get_accum_distance() const {
FILE: include/radar_graph_slam/loop_detector.hpp
type radar_graph_slam (line 24) | namespace radar_graph_slam {
type Loop (line 26) | struct Loop {
method Loop (line 31) | Loop(const KeyFrame::Ptr& key1, const KeyFrame::Ptr& key2, const Eig...
class LoopDetector (line 42) | class LoopDetector {
method LoopDetector (line 50) | LoopDetector() {}
FILE: include/radar_graph_slam/map_cloud_generator.hpp
type radar_graph_slam (line 11) | namespace radar_graph_slam {
class MapCloudGenerator (line 16) | class MapCloudGenerator {
FILE: include/radar_graph_slam/nmea_sentence_parser.hpp
type radar_graph_slam (line 12) | namespace radar_graph_slam {
type GPRMC (line 14) | struct GPRMC {
method GPRMC (line 16) | GPRMC() {
method GPRMC (line 20) | GPRMC(const std::vector<std::string>& tokens) {
method degmin2deg (line 51) | double degmin2deg(double degmin) {
class NmeaSentenceParser (line 77) | class NmeaSentenceParser {
method NmeaSentenceParser (line 79) | NmeaSentenceParser() {}
method GPRMC (line 82) | GPRMC parse(const std::string& sentence) const {
FILE: include/radar_graph_slam/polynomial_interpolation.hpp
class CubicInterpolation (line 6) | class CubicInterpolation {
method CubicInterpolation (line 10) | CubicInterpolation(Eigen::MatrixXd q_via_, Eigen::VectorXd t_via_){
method cubic (line 31) | Eigen::Vector4d cubic(double q0, double q1, double v0, double v1, doub...
method getPosition (line 59) | double getPosition(double t){
FILE: include/radar_graph_slam/registrations.hpp
type radar_graph_slam (line 10) | namespace radar_graph_slam {
FILE: include/radar_graph_slam/ros_time_hash.hpp
class RosTimeHash (line 14) | class RosTimeHash {
FILE: include/radar_graph_slam/ros_utils.hpp
type radar_graph_slam (line 14) | namespace radar_graph_slam {
function restrict_rad (line 19) | double restrict_rad(double rad){
function R2ypr (line 29) | Eigen::Vector3d R2ypr(const Eigen::Matrix3d& R) {
function matrix2transform (line 54) | static geometry_msgs::TransformStamped matrix2transform(const ros::Tim...
function matrix2odom (line 76) | static nav_msgs::Odometry matrix2odom(const ros::Time& stamp, const Ei...
function pose2isometry (line 98) | static Eigen::Isometry3d pose2isometry(const geometry_msgs::Pose& pose) {
function transform2isometry (line 105) | static Eigen::Isometry3d transform2isometry(const geometry_msgs::Trans...
function tf2isometry (line 112) | static Eigen::Isometry3d tf2isometry(const tf::StampedTransform& trans) {
function quaternion2isometry (line 119) | static Eigen::Isometry3d quaternion2isometry(const Eigen::Quaterniond&...
function isometry2pose (line 125) | static geometry_msgs::Pose isometry2pose(const Eigen::Isometry3d& mat) {
function isometry2odom (line 141) | static nav_msgs::Odometry isometry2odom(const ros::Time& stamp, const ...
function odom2isometry (line 159) | static Eigen::Isometry3d odom2isometry(const nav_msgs::OdometryConstPt...
FILE: include/rio_utils/data_types.h
function namespace (line 28) | namespace rio
function Real (line 68) | Real pitch() const { return Vector3::y(); }
function Real (line 71) | Real yaw() const { return Vector3::z(); }
function v_n_b (line 83) | NavigationSolution(const Vector3& p_n_b, const Quaternion& q_n_b, const ...
function setPosition_n_b (line 91) | void setPosition_n_b(const Vector3& p_n_b) { pose_n_b.translation() = p_...
function setQuaternion (line 95) | void setQuaternion(const Quaternion& q_n_b) { pose_n_b.linear() = q_n_b....
function EulerAngles (line 97) | EulerAngles getEuler_n_b() const
type ImuData (line 132) | struct ImuData
type ImuDataStamped (line 144) | struct ImuDataStamped
FILE: include/rio_utils/math_helper.h
function namespace (line 22) | namespace rio
function cartesianToSpherical (line 76) | static void cartesianToSpherical(const Vector3& v, Real& r, Real& azi, R...
function ConvolveType (line 86) | enum class ConvolveType
FILE: include/rio_utils/radar_point_cloud.h
function namespace (line 30) | namespace rio
type RadarPointCloudType (line 37) | struct RadarPointCloudType
type EaglePointXYZIVRAB (line 61) | struct EaglePointXYZIVRAB
FILE: include/rio_utils/ros_helper.h
function namespace (line 21) | namespace rio
FILE: include/rio_utils/simple_profiler.h
function namespace (line 29) | namespace rio
FILE: include/rio_utils/strapdown.h
function namespace (line 22) | namespace rio
FILE: include/scan_context/KDTreeVectorOfVectorsAdaptor.h
type typename (line 53) | typedef typename Distance::template traits<num_t,self_t>::distance_t met...
type nanoflann (line 54) | typedef nanoflann::KDTreeSingleIndexAdaptor< metric_t,self_t,DIM,IndexTy...
function m_data (line 59) | KDTreeVectorOfVectorsAdaptor(const size_t /* dimensionality */, const Ve...
function num_t (line 103) | inline num_t kdtree_get_pt(const size_t idx, const size_t dim) const {
FILE: include/scan_context/Scancontext.h
type PointXYZIRPYT (line 47) | struct PointXYZIRPYT
function SCInputType (line 65) | enum class SCInputType {
FILE: include/scan_context/nanoflann.hpp
function T (line 79) | T pi_const() {
type has_resize (line 87) | struct has_resize : std::false_type {}
type has_resize<T, decltype((void)std::declval<T>().resize(1), 0)> (line 90) | struct has_resize<T, decltype((void)std::declval<T>().resize(1), 0)>
type has_assign (line 93) | struct has_assign : std::false_type {}
type has_assign<T, decltype((void)std::declval<T>().assign(1, 0), 0)> (line 96) | struct has_assign<T, decltype((void)std::declval<T>().assign(1, 0), 0)>
function resize (line 103) | inline typename std::enable_if<has_resize<Container>::value, void>::type
function resize (line 113) | inline typename std::enable_if<!has_resize<Container>::value, void>::type
function assign (line 123) | inline typename std::enable_if<has_assign<Container>::value, void>::type
function assign (line 132) | inline typename std::enable_if<!has_assign<Container>::value, void>::type
class KNNResultSet (line 142) | class KNNResultSet {
method KNNResultSet (line 155) | inline KNNResultSet(CountType capacity_)
method init (line 158) | inline void init(IndexType *indices_, DistanceType *dists_) {
method CountType (line 166) | inline CountType size() const { return count; }
method full (line 168) | inline bool full() const { return count == capacity; }
method addPoint (line 175) | inline bool addPoint(DistanceType dist, IndexType index) {
type IndexDist_Sorter (line 208) | struct IndexDist_Sorter {
class RadiusResultSet (line 220) | class RadiusResultSet {
method RadiusResultSet (line 230) | inline RadiusResultSet(
method init (line 237) | inline void init() { clear(); }
method clear (line 238) | inline void clear() { m_indices_dists.clear(); }
method size (line 240) | inline size_t size() const { return m_indices_dists.size(); }
method full (line 242) | inline bool full() const { return true; }
method addPoint (line 249) | inline bool addPoint(DistanceType dist, IndexType index) {
method DistanceType (line 255) | inline DistanceType worstDist() const { return radius; }
method worst_item (line 261) | std::pair<IndexType, DistanceType> worst_item() const {
method save_value (line 279) | void save_value(FILE *stream, const T &value, size_t count = 1) {
method save_value (line 284) | void save_value(FILE *stream, const std::vector<T> &value) {
method load_value (line 291) | void load_value(FILE *stream, T &value, size_t count = 1) {
method load_value (line 298) | void load_value(FILE *stream, std::vector<T> &value) {
type Metric (line 315) | struct Metric {}
type L1_Adaptor (line 324) | struct L1_Adaptor {
method L1_Adaptor (line 330) | L1_Adaptor(const DataSource &_data_source) : data_source(_data_sourc...
method DistanceType (line 332) | inline DistanceType evalMetric(const T *a, const size_t b_idx, size_...
method DistanceType (line 363) | inline DistanceType accum_dist(const U a, const V b, const size_t) c...
type L2_Adaptor (line 375) | struct L2_Adaptor {
method L2_Adaptor (line 381) | L2_Adaptor(const DataSource &_data_source) : data_source(_data_sourc...
method DistanceType (line 383) | inline DistanceType evalMetric(const T *a, const size_t b_idx, size_...
method DistanceType (line 411) | inline DistanceType accum_dist(const U a, const V b, const size_t) c...
type L2_Simple_Adaptor (line 423) | struct L2_Simple_Adaptor {
method L2_Simple_Adaptor (line 429) | L2_Simple_Adaptor(const DataSource &_data_source)
method DistanceType (line 432) | inline DistanceType evalMetric(const T *a, const size_t b_idx,
method DistanceType (line 443) | inline DistanceType accum_dist(const U a, const V b, const size_t) c...
type SO2_Adaptor (line 455) | struct SO2_Adaptor {
method SO2_Adaptor (line 461) | SO2_Adaptor(const DataSource &_data_source) : data_source(_data_sour...
method DistanceType (line 463) | inline DistanceType evalMetric(const T *a, const size_t b_idx,
method DistanceType (line 471) | inline DistanceType accum_dist(const U a, const V b, const size_t) c...
type SO3_Adaptor (line 490) | struct SO3_Adaptor {
method SO3_Adaptor (line 496) | SO3_Adaptor(const DataSource &_data_source)
method DistanceType (line 499) | inline DistanceType evalMetric(const T *a, const size_t b_idx,
method DistanceType (line 505) | inline DistanceType accum_dist(const U a, const V b, const size_t id...
type metric_L1 (line 511) | struct metric_L1 : public Metric {
type traits (line 512) | struct traits {
type metric_L2 (line 517) | struct metric_L2 : public Metric {
type traits (line 518) | struct traits {
type metric_L2_Simple (line 523) | struct metric_L2_Simple : public Metric {
type traits (line 524) | struct traits {
type metric_SO2 (line 529) | struct metric_SO2 : public Metric {
type traits (line 530) | struct traits {
type metric_SO3 (line 535) | struct metric_SO3 : public Metric {
type traits (line 536) | struct traits {
type KDTreeSingleIndexAdaptorParams (line 547) | struct KDTreeSingleIndexAdaptorParams {
method KDTreeSingleIndexAdaptorParams (line 548) | KDTreeSingleIndexAdaptorParams(size_t _leaf_max_size = 10)
type SearchParams (line 555) | struct SearchParams {
method SearchParams (line 558) | SearchParams(int checks_IGNORED_ = 32, float eps_ = 0, bool sorted_ ...
method T (line 579) | inline T *allocate(size_t count = 1) {
class PooledAllocator (line 602) | class PooledAllocator {
method internal_init (line 613) | void internal_init() {
method PooledAllocator (line 627) | PooledAllocator() { internal_init(); }
method free_all (line 635) | void free_all() {
method T (line 703) | T *allocate(const size_t count = 1) {
type array_or_vector_selector (line 716) | struct array_or_vector_selector {
type array_or_vector_selector<-1, T> (line 720) | struct array_or_vector_selector<-1, T> {
class KDTreeBaseClass (line 740) | class KDTreeBaseClass {
method freeIndex (line 745) | void freeIndex(Derived &obj) {
type Node (line 755) | struct Node {
type leaf (line 759) | struct leaf {
type nonleaf (line 762) | struct nonleaf {
type Interval (line 772) | struct Interval {
method size (line 814) | size_t size(const Derived &obj) const { return obj.m_size; }
method veclen (line 817) | size_t veclen(const Derived &obj) {
method ElementType (line 822) | inline ElementType dataset_get(const Derived &obj, size_t idx,
method usedMemory (line 831) | size_t usedMemory(Derived &obj) {
method computeMinMax (line 837) | void computeMinMax(const Derived &obj, IndexType *ind, IndexType count,
method NodePtr (line 858) | NodePtr divideTree(Derived &obj, const IndexType left, const IndexTy...
method middleSplit_ (line 910) | void middleSplit_(Derived &obj, IndexType *ind, IndexType count,
method planeSplit (line 968) | void planeSplit(Derived &obj, IndexType *ind, const IndexType count,
method DistanceType (line 1006) | DistanceType computeInitialDistances(const Derived &obj,
method save_tree (line 1025) | void save_tree(Derived &obj, FILE *stream, NodePtr tree) {
method load_tree (line 1035) | void load_tree(Derived &obj, FILE *stream, NodePtr &tree) {
method saveIndex_ (line 1051) | void saveIndex_(Derived &obj, FILE *stream) {
method loadIndex_ (line 1065) | void loadIndex_(Derived &obj, FILE *stream) {
class KDTreeSingleIndexAdaptor (line 1117) | class KDTreeSingleIndexAdaptor
method KDTreeSingleIndexAdaptor (line 1123) | KDTreeSingleIndexAdaptor(
method KDTreeSingleIndexAdaptor (line 1171) | KDTreeSingleIndexAdaptor(const int dimensionality,
method buildIndex (line 1191) | void buildIndex() {
method findNeighbors (line 1222) | bool findNeighbors(RESULTSET &result, const ElementType *vec,
method knnSearch (line 1253) | size_t knnSearch(const ElementType *query_point, const size_t num_cl...
method radiusSearch (line 1278) | size_t
method radiusSearchCustomCallback (line 1296) | size_t radiusSearchCustomCallback(
method init_vind (line 1308) | void init_vind() {
method computeBoundingBox (line 1317) | void computeBoundingBox(BoundingBox &bbox) {
method searchLevel (line 1347) | bool searchLevel(RESULTSET &result_set, const ElementType *vec,
method saveIndex (line 1418) | void saveIndex(FILE *stream) { this->saveIndex_(*this, stream); }
method loadIndex (line 1425) | void loadIndex(FILE *stream) { this->loadIndex_(*this, stream); }
class KDTreeSingleIndexDynamicAdaptor_ (line 1467) | class KDTreeSingleIndexDynamicAdaptor_
method KDTreeSingleIndexDynamicAdaptor_ (line 1518) | KDTreeSingleIndexDynamicAdaptor_(
method KDTreeSingleIndexDynamicAdaptor_ (line 1535) | KDTreeSingleIndexDynamicAdaptor_
method buildIndex (line 1554) | void buildIndex() {
method findNeighbors (line 1583) | bool findNeighbors(RESULTSET &result, const ElementType *vec,
method knnSearch (line 1613) | size_t knnSearch(const ElementType *query_point, const size_t num_cl...
method radiusSearch (line 1638) | size_t
method radiusSearchCustomCallback (line 1656) | size_t radiusSearchCustomCallback(
method computeBoundingBox (line 1666) | void computeBoundingBox(BoundingBox &bbox) {
method searchLevel (line 1696) | void searchLevel(RESULTSET &result_set, const ElementType *vec,
method saveIndex (line 1762) | void saveIndex(FILE *stream) { this->saveIndex_(*this, stream); }
method loadIndex (line 1769) | void loadIndex(FILE *stream) { this->loadIndex_(*this, stream); }
class KDTreeSingleIndexDynamicAdaptor (line 1788) | class KDTreeSingleIndexDynamicAdaptor {
method First0Bit (line 1822) | int First0Bit(IndexType num) {
method init (line 1832) | void init() {
method KDTreeSingleIndexDynamicAdaptor (line 1857) | KDTreeSingleIndexDynamicAdaptor(const int dimensionality,
method KDTreeSingleIndexDynamicAdaptor (line 1878) | KDTreeSingleIndexDynamicAdaptor(
method addPoints (line 1883) | void addPoints(IndexType start, IndexType end) {
method removePoint (line 1906) | void removePoint(size_t idx) {
method findNeighbors (line 1926) | bool findNeighbors(RESULTSET &result, const ElementType *vec,
type KDTreeEigenMatrixAdaptor (line 1954) | struct KDTreeEigenMatrixAdaptor {
method KDTreeEigenMatrixAdaptor (line 1968) | KDTreeEigenMatrixAdaptor(const size_t dimensionality,
method KDTreeEigenMatrixAdaptor (line 1987) | KDTreeEigenMatrixAdaptor(const self_t &) = delete;
method query (line 1999) | inline void query(const num_t *query_point, const size_t num_closest,
method self_t (line 2010) | const self_t &derived() const { return *this; }
method self_t (line 2011) | self_t &derived() { return *this; }
method kdtree_get_point_count (line 2014) | inline size_t kdtree_get_point_count() const {
method num_t (line 2019) | inline num_t kdtree_get_pt(const IndexType idx, size_t dim) const {
method kdtree_get_bbox (line 2028) | bool kdtree_get_bbox(BBOX & /*bb*/) const {
FILE: include/scan_context/tictoc.h
function class (line 12) | class TicToc
function tic (line 26) | void tic()
function toc (line 31) | void toc( std::string _about_task )
FILE: include/utility_radar.h
type pcl (line 59) | typedef pcl::PointXYZI PointType;
function class (line 61) | class ParamServer
function pointDistance (line 293) | float pointDistance(PointType p)
function pointDistance (line 299) | float pointDistance(PointType p1, PointType p2)
FILE: src/g2o/robust_kernel_io.cpp
type g2o (line 12) | namespace g2o {
function kernel_type (line 14) | std::string kernel_type(g2o::RobustKernel* kernel) {
function save_robust_kernels (line 45) | bool save_robust_kernels(const std::string& filename, g2o::SparseOptim...
class KernelData (line 75) | class KernelData {
method KernelData (line 77) | KernelData(const std::string& line) {
method match (line 90) | bool match(g2o::OptimizableGraph::Edge* edge) const {
function load_robust_kernels (line 118) | bool load_robust_kernels(const std::string& filename, g2o::SparseOptim...
FILE: src/gps_traj_align.cpp
function associate (line 28) | std::vector<std::pair<int,int>> associate(std::vector<double> first_stam...
function read_topic_from_rosbag (line 96) | void read_topic_from_rosbag(rosbag::View::iterator& iter, rosbag::View& ...
function main (line 111) | int main()
FILE: src/gt_adjust.cpp
function main (line 24) | int main()
FILE: src/radar_ego_velocity_estimator.cpp
function RadarPointCloudType (line 41) | static RadarPointCloudType toRadarPointCloudType(const Vector11& item, c...
FILE: src/radar_graph_slam/Scancontext.cpp
function coreImportTest (line 7) | void coreImportTest (void)
function rad2deg (line 13) | float rad2deg(float radians)
function deg2rad (line 18) | float deg2rad(float degrees)
function xy2theta (line 24) | float xy2theta( const float & _x, const float & _y )
function MatrixXd (line 42) | MatrixXd circshift( MatrixXd &_mat, int _num_shift )
function eig2stdvec (line 73) | std::vector<float> eig2stdvec( MatrixXd _eigmat )
function MatrixXd (line 162) | MatrixXd SCManager::makeScancontext( pcl::PointCloud<SCPointType> & _sca...
function MatrixXd (line 217) | MatrixXd SCManager::makeRingkeyFromScancontext( Eigen::MatrixXd &_desc )
function MatrixXd (line 233) | MatrixXd SCManager::makeSectorkeyFromScancontext( Eigen::MatrixXd &_desc )
FILE: src/radar_graph_slam/bag_player.py
class BagPlayer (line 24) | class BagPlayer:
method __init__ (line 25) | def __init__(self, bagfile, start, duration):
method update_time_subs (line 54) | def update_time_subs(self):
method time_callback (line 61) | def time_callback(self, header_msg, topic_name):
method play_realtime (line 68) | def play_realtime(self, duration):
method print_progress (line 101) | def print_progress(self, stamp):
method check_stamp (line 147) | def check_stamp(self, topic, msg):
method play (line 165) | def play(self):
function main (line 207) | def main():
FILE: src/radar_graph_slam/ford2bag.py
function gps2navsat (line 19) | def gps2navsat(filename, bag):
function mat2pointcloud (line 59) | def mat2pointcloud(filename):
function main (line 71) | def main():
FILE: src/radar_graph_slam/graph_slam.cpp
type g2o (line 36) | namespace g2o {
type radar_graph_slam (line 53) | namespace radar_graph_slam {
FILE: src/radar_graph_slam/information_matrix_calculator.cpp
type radar_graph_slam (line 12) | namespace radar_graph_slam {
FILE: src/radar_graph_slam/keyframe.cpp
type radar_graph_slam (line 11) | namespace radar_graph_slam {
FILE: src/radar_graph_slam/loop_detector.cpp
function R2ypr_ (line 5) | Eigen::Vector3d R2ypr_(const Eigen::Matrix3d& R) {
function limit_value (line 21) | double limit_value(int value, int min_, int max_){
function monoToRainbow (line 29) | Eigen::Vector3d monoToRainbow(int value){
type radar_graph_slam (line 48) | namespace radar_graph_slam {
FILE: src/radar_graph_slam/map2odom_publisher.py
class Map2OdomPublisher (line 8) | class Map2OdomPublisher:
method __init__ (line 9) | def __init__(self):
method callback (line 13) | def callback(self, odom_msg):
method spin (line 16) | def spin(self):
function main (line 31) | def main():
FILE: src/radar_graph_slam/map_cloud_generator.cpp
type radar_graph_slam (line 7) | namespace radar_graph_slam {
FILE: src/radar_graph_slam/registrations.cpp
type radar_graph_slam (line 21) | namespace radar_graph_slam {
function select_registration_method (line 23) | pcl::Registration<pcl::PointXYZI, pcl::PointXYZI>::Ptr select_registra...
Condensed preview — 79 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (543K chars).
[
{
"path": "CMakeLists.txt",
"chars": 5425,
"preview": "# SPDX-License-Identifier: BSD-2-Clause\ncmake_minimum_required(VERSION 2.8.3)\nproject(radar_graph_slam)\n\n# Can we use C+"
},
{
"path": "LICENSE",
"chars": 35149,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
},
{
"path": "README.md",
"chars": 7797,
"preview": "# 4DRadarSLAM\n## A 4D Imaging Radar SLAM System for Large-scale Environments based on Pose Graph Optimization\n\n[Paper (R"
},
{
"path": "apps/preprocessing_nodelet.cpp",
"chars": 24627,
"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <string>\n#include <fstream>\n#include <functional>\n\n#include <ros/ros."
},
{
"path": "apps/radar_graph_slam_nodelet.cpp",
"chars": 59427,
"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <ctime>\n#include <mutex>\n#include <atomic>\n#include <memory>\n#include"
},
{
"path": "apps/scan_matching_odometry_nodelet.cpp",
"chars": 34806,
"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <ctime>\n#include <chrono>\n#include <mutex>\n#include <atomic>\n#include"
},
{
"path": "cmake/FindG2O.cmake",
"chars": 3443,
"preview": "# Find the header files\n\nFIND_PATH(G2O_INCLUDE_DIR g2o/core/base_vertex.h\n ${G2O_ROOT}/include\n $ENV{G2O_ROOT}/include"
},
{
"path": "config/params.yaml",
"chars": 2483,
"preview": "radar_slam:\n\n # Topics\n pointCloudTopic: \"/radar_enhanced_pcl\" # Point cloud data <!-- pc2_raw inlier_pc"
},
{
"path": "include/dbscan/DBSCAN_kdtree.h",
"chars": 512,
"preview": "#ifndef DBSCAN_KDTREE_H\n#define DBSCAN_KDTREE_H\n\n#include <pcl/point_types.h>\n#include \"DBSCAN_simple.h\"\n\ntemplate <type"
},
{
"path": "include/dbscan/DBSCAN_precomp.h",
"chars": 2211,
"preview": "#ifndef DBSCAN_PRECOMP_H\n#define DBSCAN_PRECOMP_H\n\n#include <pcl/point_types.h>\n#include \"DBSCAN_simple.h\"\n\ntemplate <ty"
},
{
"path": "include/dbscan/DBSCAN_simple.h",
"chars": 5405,
"preview": "#ifndef DBSCAN_H\n#define DBSCAN_H\n\n#include <pcl/point_types.h>\n\n#define UN_PROCESSED 0\n#define PROCESSING 1\n#define PRO"
},
{
"path": "include/g2o/edge_plane_identity.hpp",
"chars": 3347,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
{
"path": "include/g2o/edge_plane_parallel.hpp",
"chars": 4853,
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"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
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"path": "include/g2o/edge_se3_gt_utm.hpp",
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"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
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"path": "include/g2o/edge_se3_plane.hpp",
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"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
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"path": "include/g2o/edge_se3_priorquat.hpp",
"chars": 3091,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
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"path": "include/g2o/edge_se3_priorvec.hpp",
"chars": 3177,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
{
"path": "include/g2o/edge_se3_priorxy.hpp",
"chars": 2826,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
{
"path": "include/g2o/edge_se3_priorxyz.hpp",
"chars": 2833,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
{
"path": "include/g2o/edge_se3_priorz.hpp",
"chars": 2868,
"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
},
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"path": "include/g2o/edge_se3_se3.hpp",
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"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
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"preview": "// g2o - General Graph Optimization\n// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard\n// All rights reserved.\n"
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#ifndef ROBUST_KERNEL_IO_HPP\n#define ROBUST_KERNEL_IO_HPP\n\n#include <string>\n#"
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"path": "include/radar_ego_velocity_estimator.h",
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"path": "include/radar_graph_slam/graph_slam.hpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#ifndef GRAPH_SLAM_HPP\n#define GRAPH_SLAM_HPP\n\n#include <memory>\n#include <ros"
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"path": "include/radar_graph_slam/information_matrix_calculator.hpp",
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"path": "include/radar_graph_slam/map_cloud_generator.hpp",
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"path": "include/radar_graph_slam/nmea_sentence_parser.hpp",
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"path": "include/radar_graph_slam/polynomial_interpolation.hpp",
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"preview": "\n#include <ros/ros.h>\n\n#include <Eigen/Dense>\n\nclass CubicInterpolation {\n public:\n Eigen::MatrixXd q_via;\n Eig"
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"path": "include/radar_graph_slam/registrations.hpp",
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"path": "include/rio_utils/data_types.h",
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"path": "include/rio_utils/radar_point_cloud.h",
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"path": "include/rio_utils/ros_helper.h",
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"path": "include/rio_utils/simple_profiler.h",
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"path": "include/rio_utils/strapdown.h",
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"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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"path": "include/scan_context/KDTreeVectorOfVectorsAdaptor.h",
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"preview": "/***********************************************************************\n * Software License Agreement (BSD License)\n *\n"
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"preview": "/***********************************************************************\n * Software License Agreement (BSD License)\n *\n"
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"preview": "// Author: Tong Qin qintonguav@gmail.com\n// \t Shaozu Cao \t\t saozu.cao@connect.ust.hk\n\n#pragma"
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"path": "include/utility_radar.h",
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"preview": "#pragma once\n#ifndef _UTILITY_RADAR_ODOMETRY_H_\n#define _UTILITY_RADAR_ODOMETRY_H_\n\n#include <ros/ros.h>\n\n#include <std_"
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"path": "launch/radar_graph_slam.launch",
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"path": "launch/rosbag_play_radar_carpark1.launch",
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"path": "setup.py",
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"preview": "## ! DO NOT MANUALLY INVOKE THIS setup.py, USE CATKIN INSTEAD\n\nfrom setuptools import setup\nfrom catkin_pkg.python_setup"
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"path": "src/g2o/robust_kernel_io.cpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <g2o/robust_kernel_io.hpp>\n\n#include <fstream>\n#include <iostream>\n#i"
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"path": "src/gps_traj_align.cpp",
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"preview": "#include <stdio.h>\n\n#include <algorithm>\n#include <iostream>\n#include <fstream>\n#include <string>\n#include <vector>\n#inc"
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"path": "src/radar_ego_velocity_estimator.cpp",
"chars": 11839,
"preview": "// This file is part of RIO - Radar Inertial Odometry and Radar ego velocity estimation.\n// Copyright (C) 2021 Christop"
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{
"path": "src/radar_graph_slam/Scancontext.cpp",
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"preview": "#include \"scan_context/Scancontext.h\"\n\n// namespace SC2\n// {\nusing namespace radar_graph_slam;\n\nvoid coreImportTest (voi"
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{
"path": "src/radar_graph_slam/__init__.py",
"chars": 0,
"preview": ""
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"preview": "#!/usr/bin/python\n# SPDX-License-Identifier: BSD-2-Clause\nimport sys\nimport yaml\nimport time\nimport curses\nimport argpar"
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"path": "src/radar_graph_slam/ford2bag.py",
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"preview": "#!/usr/bin/python\n# SPDX-License-Identifier: BSD-2-Clause\nimport re\nimport os\nimport sys\nimport struct\nimport numpy\nimpo"
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"path": "src/radar_graph_slam/graph_slam.cpp",
"chars": 14536,
"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <radar_graph_slam/graph_slam.hpp>\n\n#include <boost/format.hpp>\n#inclu"
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"path": "src/radar_graph_slam/information_matrix_calculator.cpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <iostream>\n\n#include <radar_graph_slam/information_matrix_calculator."
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"path": "src/radar_graph_slam/keyframe.cpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <radar_graph_slam/keyframe.hpp>\n\n#include <boost/filesystem.hpp>\n\n#in"
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{
"path": "src/radar_graph_slam/loop_detector.cpp",
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"preview": "#include <radar_graph_slam/loop_detector.hpp>\n\nusing namespace std;\n\nEigen::Vector3d R2ypr_(const Eigen::Matrix3d& R) {\n"
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"path": "src/radar_graph_slam/map2odom_publisher.py",
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"preview": "#!/usr/bin/python\n# SPDX-License-Identifier: BSD-2-Clause\nimport tf\nimport rospy\nfrom geometry_msgs.msg import *\n\n\nclass"
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"path": "src/radar_graph_slam/map_cloud_generator.cpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <radar_graph_slam/map_cloud_generator.hpp>\n\n#include <pcl/octree/octr"
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"path": "src/radar_graph_slam/registrations.cpp",
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"preview": "// SPDX-License-Identifier: BSD-2-Clause\n\n#include <radar_graph_slam/registrations.hpp>\n\n#include <iostream>\n\n#include <"
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{
"path": "srv/DumpGraph.srv",
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"preview": "\nstring destination\n---\nbool success\n"
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"path": "srv/SaveMap.srv",
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"preview": "bool utm\nfloat32 resolution\nstring destination\n---\nbool success\n"
}
]
About this extraction
This page contains the full source code of the zhuge2333/4DRadarSLAM GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 79 files (508.8 KB), approximately 143.8k tokens, and a symbol index with 453 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.