Repository: wanghuayou1028/ICRA2021-SLAM-paper-list Branch: main Commit: 433633ba66d5 Files: 1 Total size: 27.2 KB Directory structure: gitextract_jirk81_h/ └── README.md ================================================ FILE CONTENTS ================================================ ================================================ FILE: README.md ================================================ # ICRA2021-SLAM-paper-list All the classified papers can be download from Baidu cloud Disk: Link:https://pan.baidu.com/s/1NplHJezNTN_YetYmqI0qUg passwork:gban ## Semantic localization and mapping: 1. Visual Semantic Localization Based on HD Map for Autonomous Vehicles in Urban Scenarios 2. RoadMap: A Light-Weight Semantic Map for Visual Localization towards Autonomous Driving 3. Road Mapping and Localization Using Sparse Semantic Visual Features https://ieeexplore.ieee.org/document/9387091 4. Kimera-Multi: A System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping https://arxiv.org/abs/2011.04087 5. Semantic SLAM with Autonomous Object-Level Data Association https://arxiv.org/abs/2011.10625 6. Hybrid Bird's-Eye Edge Based Semantic Visual SLAM for Automated Valet Parking (AVP) https://www.zhenzhenxiang.xyz/publication/icra2021/ 7. Compositional and Scalable Object SLAM https://arxiv.org/abs/2011.02658 8. Robust Semantic Map Matching Algorithm Based on Probabilistic Registration Model 9. Semantically Guided Multi-View Stereo for Dense 3D Road Mapping 10. Robust Improvement in 3D Object Landmark Inference for Semantic Mapping 11. Any Way You Look at It: Semantic Crossview Localization and Mapping with LiDAR https://github.com/iandouglas96/cross_view_slam / https://ieeexplore.ieee.org/document/9361130 12. PSF-LO: Parameterized Semantic Features Based Lidar Odometry https://arxiv.org/abs/2010.13355 13. Point Set Registration with Semantic Region Association Using Cascaded Expectation Maximization ## Visual SLAM #### Visual SLAM 1. Asynchronous Multi-View SLAM https://arxiv.org/abs/2101.06562 2. B-Splines for Purely Vision-Based Localization and Mapping on Non-Holonomic Ground Vehicles 3. UPSLAM: Union of Panoramas SLAM https://arxiv.org/abs/2101.00585 4. Multi-Parameter Optimization for a Robust RGB-D SLAM System 5. SD-DefSLAM: Semi-Direct Monocular SLAM for Deformable and Intracorporeal Scenes https://arxiv.org/abs/2010.09409 6. MOLTR: Multiple Object Localisation, Tracking and Reconstruction from Monocular RGB Videos https://arxiv.org/abs/2012.05360 7. ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames https://arxiv.org/abs/2103.15068 8. Markov Parallel Tracking and Mapping for Probabilistic SLAM 9. Avoiding Degeneracy for Monocular Visual SLAM with Point and Line Features https://arxiv.org/abs/2103.01501 10. Learning a State Representation and Navigation in Cluttered and Dynamic Environments https://arxiv.org/pdf/2103.04351 11. TT-SLAM: Dense Monocular SLAM for Planar Environments https://hal.inria.fr/hal-03169199/ 12. OV2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications https://arxiv.org/abs/2102.04060 13. DOT: Dynamic Object Tracking for Visual SLAM https://arxiv.org/abs/2010.00052 14. DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequences (I) https://arxiv.org/abs/1908.08918 15. RGB-D SLAM with Structural Regularities https://arxiv.org/abs/2010.07997 16. RigidFusion: Robot Localisation and Mapping in Environments with Large Dynamic Rigid Objects 17. CAROM - Vehicle Localization and Traffic Scene Reconstruction from Monocular Cameras on Road Infrastructures https://arxiv.org/abs/2104.00893 18. VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough https://arxiv.org/abs/2104.06800 19. Kimera-Multi: A System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping https://arxiv.org/abs/2011.04087 #### VO: 1. Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry https://arxiv.org/abs/2101.05995 2. Accurate and Robust Stereo Direct Visual Odometry for Agricultural Environment 3. Deep Online Correction for Monocular Visual Odometry https://arxiv.org/abs/2103.10029 4. A Heteroscedastic Likelihood Model for Two-Frame Optical Flow https://arxiv.org/abs/2010.06871 5. Learning Optical Flow with R-CNN for Visual Odometry 6. Optimizing RGB-D Fusion for Accurate 6DoF Pose Estimation https://ieeexplore.ieee.org/abstract/document/9361135/ 7. Tight Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry https://arxiv.org/abs/2102.01191 8. Continuous Scale-Space Direct Image Alignment for Visual Odometry from RGB-D Images https://hal.archives-ouvertes.fr/hal-03130945/document 9. A Front-End for Dense Monocular SLAM Using a Learned Outlier Mask Prior #### Visual Mapping: 1. Structure Reconstruction Using Ray-Point-Ray Features: Representation and Camera Pose Estimation 2. Hough2Map – Iterative Event-Based Hough Transform for High-Speed Railway Mapping https://arxiv.org/pdf/2102.08145.pdf / https://github.com/ethz-asl/Hough2Map 3. Lightweight Semantic Mesh Mapping for Autonomous Vehicles 4. Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior https://arxiv.org/abs/2102.05212 5. Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning https://arxiv.org/abs/2101.01844 6. Direct Sparse Mapping (I)https://arxiv.org/abs/1904.06577 / https://github.com/jzubizarreta/dsm 7. HyperMap: Compressed 3D Map for Monocular Camera Registration https://www.cs.cmu.edu/~kaess/pub/Chang21icra.pdf 8. Probabilistic Multi-View Fusion of Active Stereo Depth Maps for Robotic Bin-Picking https://arxiv.org/abs/2103.10968 9. Reconstructing Interactive 3D Scenes by Panoptic Mapping and CAD Model Alignments https://arxiv.org/abs/2103.16095 ## VIO: 1. UVIP: Robust UWB Aided Visual-Inertial Positioning System for Complex Indoor Environments 2. Range-Focused Fusion of Camera-IMU-UWB for Accurate and Drift-Reduced Localization https://ieeexplore.ieee.org/abstract/document/9350155 3. CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth https://arxiv.org/abs/2012.10133 4. Direct Sparse Stereo Visual-Inertial Global Odometry 5. Collaborative Visual Inertial SLAM for Multiple Smart Phones 6. VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation https://arxiv.org/abs/2011.03993 7. Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle https://arxiv.org/abs/2103.01655 8. Bidirectional Trajectory Computation for Odometer-Aided Visual-Inertial SLAM https://arxiv.org/abs/2002.00195 9. Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements https://arxiv.org/abs/2010.11675 10. An Equivariant Filter for Visual Inertial Odometry https://arxiv.org/abs/2104.03532 11. Revisiting Visual-Inertial Structure-From-Motion for Odometry and SLAM Initialization https://arxiv.org/abs/2006.06017 12. Cooperative Visual-Inertial Odometry https://hal.inria.fr/hal-02427991/document ## Tracking: 1. Tracking 6-DoF Object Motion from Events and Frames https://arxiv.org/abs/2103.15568 2. Visual Tracking of Deforming Objects Using Physics-Based Models https://hal.inria.fr/hal-03179253/document 3. Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping https://arxiv.org/abs/2103.05401 4. TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction ## Depth estimation: 1. Robust Monocular Visual-Inertial Depth Completion for Embedded Systems http://udel.edu/~pgeneva/downloads/papers/c19.pdf 2. Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation https://arxiv.org/abs/2103.02451 3. SelfDeco: Self-Supervised Monocular Depth Completion in Challenging Indoor Environments https://arxiv.org/abs/2011.04977 4. Stereo-Augmented Depth Completion from a Single RGB-LiDAR Image 5. PENet: Towards Precise and Efficient Image Guided Depth Completion https://arxiv.org/abs/2103.00783 / https://github.com/JUGGHM/PENet_ICRA2021 6. Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation https://arxiv.org/abs/2103.12964 7. PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation https://arxiv.org/abs/2006.02068 8. Bidirectional Attention Network for Monocular Depth Estimation https://arxiv.org/abs/2009.00743 9. Self-Guided Instance-Aware Network for Depth Completion and Enhancement 10. Deep Multi-View Depth Estimation with Predicted Uncertainty https://arxiv.org/abs/2011.09594 11. MultiViewStereoNet: Fast Multi-View Stereo Depth Estimation Using Incremental Viewpoint-Compensated Feature Extraction 12. Linear Inverse Problem for Depth Completion with RGB Image and Sparse LIDAR Fusion 13. Toward Robust and Efficient Online Adaptation for Deep Stereo Depth Estimation ## Visual place recognition: 1. Intelligent Reference Curation for Visual Place Recognition Via Bayesian Selective Fusion https://arxiv.org/abs/2010.09228 2. Appearance-Based Loop Closure Detection Via Bidirectional Manifold Representation Consensus 3. SoftMP: Attentive Feature Pooling for Joint Local Feature Detection and Description for Place Recognition in Changing Environments 4. Simultaneous Multi-Level Descriptor Learning and Semantic Segmentation for Domain-Specific Relocalization 5. Resolving Place Recognition Inconsistencies Using Intra-Set Similarities https://ieeexplore.ieee.org/abstract/document/9359453/ 6. Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems https://arxiv.org/abs/2104.10067 7. Retrieval and Localization with Observation Constraints 8. A Flexible and Efficient Loop Closure Detection Based on Motion Knowledge 9. Semantic Reinforced Attention Learning for Visual Place Recognition 10. STA-VPR: Spatio-Temporal Alignment for Visual Place Recognition https://arxiv.org/abs/2103.13580 11. Visual Place Recognition Via Local Affine Preserving Matching ## lidar place recognition: 1. DiSCO: Differentiable Scan Context with Orientation https://arxiv.org/abs/2010.10949 2. Robust Place Recognition Using an Imaging Lidar https://arxiv.org/abs/2103.02111 3. Locus: LiDAR-Based Place Recognition Using Spatiotemporal Higher-Order Pooling https://arxiv.org/abs/2011.14497 4. Resolving Place Recognition Inconsistencies Using Intra-Set Similarities https://ieeexplore.ieee.org/document/9359453/ 5. Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition https://arxiv.org/abs/2103.08366 6. Place Recognition in Forests with Urquhart Tessellations http://arxiv.org/pdf/2010.03026 ## multi-sensor fusion localization: 1. LVI-SAM: Tightly-Coupled Lidar-Visual-Inertial Odometry Via Smoothing and Mapping https://arxiv.org/abs/2104.10831 / https://github.com/TixiaoShan/LVI-SAM 2. MSTSL: Multi-Sensor Based Two-Step Localization in Geometrically Symmetric Environments 3. LatentSLAM: Unsupervised Multi-Sensor Representation Learning for Localization and Mapping https://arxiv.org/abs/2105.03265 4. Visual-Laser-Inertial SLAM Using a Compact 3D Scanner for Confined Space 5. Efficient Multi-Sensor Aided Inertial Navigation with Online Calibration 6. Range-Visual-Inertial Odometry: Scale Observability without Excitation https://arxiv.org/pdf/2103.15215 7. Airflow-Inertial Odometry for Resilient State Estimation on Multirotors 8. Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments 9. Interval-Based Visual-LiDAR Sensor Fusion https://www.researchgate.net/publication/349141103_Interval-Based_Visual-LiDAR_Sensor_Fusion 10. CamVox: A Low-Cost and Accurate Lidar-Assisted Visual SLAM System https://arxiv.org/abs/2011.11357 11. Multi-Session Underwater Pose-Graph SLAM Using Inter-Session Opti-Acoustic Two-View Factor https://irap.kaist.ac.kr/publications/hsjang-2021-icra.pdf 12. Simple but Effective Redundant Odometry for Autonomous Vehicles https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/reinke2021icra.pdf 13. Markov Localisation Using Heatmap Regression and Deep Convolutional Odometry https://cvssp.org/Personal/OscarMendez/papers/pdf/MendezICRA2021.pdf 14. Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry https://arxiv.org/abs/2011.06838 15. Vanishing Point Aided LiDAR-Visual-Inertial Estimator https://people.inf.ethz.ch/pomarc/pubs/CamposecoICRA15.pdf 16. Any Way You Look at It: Semantic Crossview Localization and Mapping with LiDAR https://github.com/iandouglas96/cross_view_slam / https://ieeexplore.ieee.org/document/9361130 ## multi-sensor fusion mapping: 1. Lidar-Monocular Surface Reconstruction Using Line Segments https://arxiv.org/abs/2104.02761 2. Automatic Mapping of Tailored Landmark Representations for Automated Driving and Map Learning ## Lidar SLAM #### lidar SLAM 1. SA-LOAM: Semantic-Aided LiDAR SLAM with Loop Closure 2. Greedy-Based Feature Selection for Efficient LiDAR SLAM https://arxiv.org/abs/2103.13090 3. Inertial Aided 3D LiDAR SLAM with Hybrid Geometric Primitives in Large-Scale Environments 4. π-LSAM: LiDAR Smoothing and Mapping with Planes 5. R-LOAM: Improving LiDAR Odometry and Mapping with Point-To-Mesh Features of a Known 3D Reference Object https://ieeexplore.ieee.org/document/9357902 6. LoLa-SLAM: Low-Latency LiDAR SLAM Using Continuous Scan Slicing https://ieeexplore.ieee.org/document/9359468 7. LiTAMIN2: Ultra Light LiDAR-Based SLAM Using Geometric Approximation Applied with KL-Divergence https://arxiv.org/abs/2103.00784 8. 2D Laser SLAM with Closed Shape Features: Fourier Series Parameterization and Submap Joining 9. Intensity-SLAM: Intensity Assisted Localization and Mapping for Large Scale Environment https://arxiv.org/abs/2102.03798 10. Online Range-Based SLAM Using B-Spline Surfaces https://welcome.isr.tecnico.ulisboa.pt/wp-content/uploads/2021/03/09359349.pdf 11. MULLS: Versatile LiDAR SLAM Via Multi-Metric Linear Least Square https://arxiv.org/abs/2102.03771 / https://github.com/YuePanEdward/MULLS 12. Dynamic Object Aware LiDAR SLAM Based on Automatic Generation of Training Data https://arxiv.org/abs/2104.03657 13. A FastSLAM Approach Integrating Beamforming Maps for Ultrasound-Based Robotic Inspection of Metal Structures https://hal.archives-ouvertes.fr/hal-03017841/document #### lidar localization: 1. Robust LiDAR Feature Localization for Autonomous Vehicles Using Geometric Fingerprinting on Open Datasets https://github.com/dcmlr/fingerprint-localization / https://ieeexplore.ieee.org/abstract/document/9363614/ 2. Robust SRIF-Based LiDAR-IMU Localization for Autonomous Vehicles 3. NDT-Transformer: Large-Scale 3D Point Cloud Localisation Using the Normal Distribution Transform Representation https://arxiv.org/abs/2103.12292 4. Connecting Semantic Building Information Models and Robotics: An Application to 2D LiDAR-Based Localization #### lidar mapping: 1. BALM: Bundle Adjustment for Lidar Mapping https://arxiv.org/pdf/2010.08215 2. Accelerating Probabilistic Volumetric Mapping Using Ray-Tracing Graphics Hardware https://arxiv.org/abs/2011.10348 3. ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building https://arxiv.org/abs/2103.04316 4. Multiresolution Representations for Large-Scale Terrain with Local Gaussian Process Regression 5. Kernel-Based 3-D Dynamic Occupancy Mapping with Particle Tracking 6. Poisson Surface Reconstruction for LiDAR Odometry and Mapping https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2021icra.pdf 7. Dynamic Occupancy Grid Mapping with Recurrent Neural Networks https://arxiv.org/abs/2011.08659 8. Semantic Mapping of Construction Site from Multiple Daily Airborne LiDAR Data https://ieeexplore.ieee.org/document/9364688/ 9. Multi-Resolution 3D Mapping with Explicit Free Space Representation for Fast and Accurate Mobile Robot Motion Planning https://arxiv.org/abs/2010.07929 10. MCMC Occupancy Grid Mapping with a Data-Driven Patch Prior 11. Elastic and Efficient LiDAR Reconstruction for Large-Scale Exploration Tasks https://arxiv.org/abs/2010.09232 #### LO & LIO: 1. FAST-LIO: A Fast, Robust LiDAR-Inertial Odometry Package by Tightly-Coupled Iterated Kalman Filter https://arxiv.org/abs/2010.08196 2. KFS-LIO: Key-Feature Selection for Lightweight Lidar Inertial Odometry 3. LIRO: Tightly Coupled Lidar-Inertia-Ranging Odometry https://arxiv.org/abs/2010.13072 4. PSF-LO: Parameterized Semantic Features Based Lidar Odometry https://arxiv.org/abs/2010.13355 5. ENCODE: A dEep poiNt Cloud ODometry NEtwork 6. Automatic Hyper-Parameter Tuning for Black-Box LiDAR Odometry 7. Self-Supervised Learning of LiDAR Odometry for Robotic Applications https://arxiv.org/pdf/2011.05418 #### Point Cloud Registration: 1. PHASER: A Robust and Correspondence-Free Global Pointcloud Registration https://arxiv.org/abs/2102.02767 2. Differential Information Aided 3-D Registration for Accurate Navigation and Scene Reconstruction https://www.researchgate.net/publication/349678605_Differential_Information_Aided_3-D_Registration_for_Accurate_Navigation_and_Scene_Reconstruction/link/603be223299bf1cc26fbc4c3/download 3. Robust Motion Averaging under Maximum Correntropy Criterion https://arxiv.org/pdf/2004.09829 4. Toward a Unified Framework for Point Set Registration http://cvl.ist.osaka-u.ac.jp/wp-content/uploads/2021/03/li_icra2021.pdf 5. Voxelized GICP for Fast and Accurate 3D Point Cloud Registration https://easychair.org/publications/preprint/ftvV 6. Probabilistic Scan Matching: Bayesian Pose Estimation from Point Clouds 7. Learning the Next Best View for 3D Point Clouds Via Topological Features https://arxiv.org/abs/2103.02789 8. A New Framework for Registration of Semantic Point Clouds from Stereo and RGB-D Cameras https://arxiv.org/abs/2012.03683 #### feature: 1. SKD: Keypoint Detection for Point Clouds Using Saliency Estimation https://arxiv.org/abs/1912.04943 2. Unsupervised Learning of Lidar Features for Use in a Probabilistic Trajectory Estimator https://arxiv.org/pdf/2102.11261 #### Solid-state lidar: 1. Lightweight 3-D Localization and Mapping for Solid-State LiDAR https://arxiv.org/abs/2102.03800 #### Point cloud compression: 1. Deep Compression for Dense Point Cloud Maps https://github.com/PRBonn/deep-point-map-compression / https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/wiesmann2021ral.pdf ## Global localization: 1. Robust LiDAR Feature Localization for Autonomous Vehicles Using Geometric Fingerprinting on Open Datasets https://github.com/dcmlr/fingerprint-localization / https://ieeexplore.ieee.org/document/9363614 2. Learned Uncertainty Calibration for Visual Inertial Localization 3. Deep Samplable Observation Model for Global Localization and Kidnapping https://arxiv.org/abs/2009.00211 4. Camera Relocalization Using Deep Point Cloud Generation and Hand-Crafted Feature Refinement 5. Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment https://arxiv.org/abs/2010.09297 6. LiDAR-Based Initial Global Localization Using Two-Dimensional (2D) Submap Projection Image (SPI) 7. Global Aerial Localisation Using Image and Map Embeddings 8. Range Image-Based LiDAR Localization for Autonomous Vehicles https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/chen2021icra.pdf 9. RadarLoc: Learning to Relocalize in FMCW Radar https://arxiv.org/abs/2103.11562 10. Freetures: Localization in Signed Distance Function Maps https://arxiv.org/abs/2010.09378 11. Self-Supervised Learning of Domain-Invariant Local Features for Robust Visual Localization under Challenging Conditions https://ieeexplore.ieee.org/abstract/document/9354898/ 12. Learning to Localize in New Environments from Synthetic Training Data https://arxiv.org/abs/2011.04539 13. Tightly-Coupled Multi-Sensor Fusion for Localization with LiDAR Feature Maps 14. Robust Dual Quadric Initialization for Forward-Translating Camera Movements https://ieeexplore.ieee.org/document/9384189 15. 3D Surfel Map-Aided Visual Relocalization with Learned Descriptors https://arxiv.org/abs/2104.03856 ## Learning-based: 1. End-To-End Semi-Supervised Learning for Differentiable Particle Filters https://arxiv.org/abs/2011.05748 2. Initialisation of Autonomous Aircraft Visual Inspection Systems Via CNN-Based Camera Pose Estimation ## Radar: 1. Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation? https://github.com/keenan-burnett/yeti_radar_odometry / https://www.semanticscholar.org/paper/Do-We-Need-to-Compensate-for-Motion-Distortion-and-Burnett-Schoellig/1f20dab73a7e04c4f8dc801bd1de104b808a07db / https://arxiv.org/pdf/2011.03512 2. RadarLoc: Learning to Relocalize in FMCW Radar https://arxiv.org/abs/2103.11562 3. A Normal Distribution Transform-Based Radar Odometry Designed for Scanning and Automotive Radars ## Data association: 1. CLEAR: A Consistent Lifting, Embedding, and Alignment Rectification Algorithm for Multiview Data Association (I) https://arxiv.org/abs/1902.02256 2. ROBIN: A Graph-Theoretic Approach to Reject Outliers in Robust Estimation Using Invariants https://arxiv.org/abs/2011.03659 3. CLIPPER: A Graph-Theoretic Framework for Robust Data Association https://arxiv.org/abs/2011.10202 ## Back-end: 1. NF-iSAM: Incremental Smoothing and Mapping Via Normalizing Flows 2. A Switching-Coupled Backend for Simultaneous Localization and Dynamic Object Tracking ## Distributed SLAM: 1. Distributed Client-Server Optimization for SLAM with Limited On-Device Resources https://arxiv.org/abs/2103.14303 2. Invariant Extended Kalman Filtering Using Two Position Receivers for Extended Pose Estimation https://arxiv.org/abs/2104.14711 3. Compartmentalized Covariance Intersection: A Novel Filter Architecture for Distributed Localization 4. Towards Robust State Estimation by Boosting the Maximum Correntropy Criterion Kalman Filter with Adaptive Behaviors https://arxiv.org/abs/2103.15354 5. Vehicle-To-Vehicle Collaborative Graph-Based Proprioceptive Localization https://scholar.google.com/scholar?oi=bibs&hl=es&cluster=16177649896940716005 ## long-term: 1. Lifelong Localization in Semi-Dynamic Environment ## Calibration: 1. Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments http://link.zhihu.com/?target=https%3A//ieeexplore.ieee.org/document/9361153 2. Efficient Online Calibration for Autonomous Vehicle's Longitudinal Dynamical System: A Gaussian Model Approach 3. Automated Extrinsic Calibration for 3D LiDARs with Range Offset Correction Using an Arbitrary Planar Board 4. Targetless Multiple Camera-LiDAR Extrinsic Calibration Using Object Pose Estimation 5. Online Photometric Calibration of Automatic Gain Thermal Infrared Cameras https://arxiv.org/abs/2012.14292 6. A Continuous-Time Approach for 3D Radar to Camera Extrinsic Calibration https://arxiv.org/abs/2103.07505 7. Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching https://arxiv.org/abs/2102.04341 8. Auto-Calibration Method Using Stop Signs for Urban Autonomous Driving Applications https://arxiv.org/abs/2010.07441 ## UWB: 1. Bias Compensated UWB Anchor Initialization Using Information-Theoretic Supported Triangulation Points https://www.aau.at/wp-content/uploads/2021/03/UWB_Initialization_ICRA_CNS.pdf 2. Relative Position Estimation between Two UWB Devices with IMUs https://arxiv.org/abs/2104.10730 3. UWB Indoor Global Localisation for Nonholonomic Robots with Unknown Offset Compensation 4. Consistent State Estimation on Manifolds for Autonomous Metal Structure Inspection https://www.researchgate.net/profile/Alessandro-Fornasier/publication/350459466_Consistent_State_Estimation_on_Manifolds_for_Autonomous_Metal_Structure_Inspection/links/6061b364a6fdccbfea147687/Consistent-State-Estimation-on-Manifolds-for-Autonomous-Metal-Structure-Inspection.pdf ## Math related: 1. Efficient Modification of the Upper Triangular Square Root Matrix on Variable Reordering https://www.researchgate.net/publication/347950562_Efficient_Modification_of_the_Upper_Triangular_Square_Root_Matrix_on_Variable_Reordering/link/6009d60a92851c13fe2a8084/download 2. Robust 360-8PA: Redesigning the Normalized 8-Point Algorithm for 360-FoV Images https://arxiv.org/abs/2104.10900 ## Dataset: 1. RADIATE: A Radar Dataset for Automotive Perception in Bad Weather https://arxiv.org/pdf/2010.09076 2. Cirrus: A Long-Range Bi-Pattern LiDAR Dataset https://arxiv.org/abs/2012.02938 3. VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments https://github.com/kminoda/VIODE / https://www.semanticscholar.org/paper/VIODE%3A-A-Simulated-Dataset-to-Address-the-of-in-Minoda-Schilling/2f339961731cbaedf54d71f874541a5894ef5a15 4. A Multi-Spectral Dataset for Evaluating Motion Estimation Systems https://arxiv.org/abs/2007.00622 5. PicoVO: A Lightweight RGB-D Visual Odometry Targeting Resource-Constrained IoT Devices 6. Are We Ready for Unmanned Surface Vehicles in Inland Waterways? the USVInland Multisensor Dataset and Benchmark https://arxiv.org/abs/2103.05383 7. DSEC: A Stereo Event Camera Dataset for Driving Scenarios https://arxiv.org/abs/2103.06011 8. AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild https://github.com/African-Robotics-Unit/AcinoSet / https://arxiv.org/abs/2103.13282 ## Medical localization: 1. Robotically Surgical Vessel Localization Using Robust Hybrid Video Motion Magnification https://ieeexplore.ieee.org/document/9353981 ## Sound source localization: 1. GCC-PHAT with Speech-Oriented Attention for Robotic Sound Source Localization ## GNSS: 1. Towards Robust GNSS Positioning and Real-Time Kinematic Using Factor Graph Optimization ## UAV: 1. Tracking and Relative Localization of Drone Swarms with a Vision-Based Headset https://ieeexplore.ieee.org/document/9324934 2. UAV Localization Using Autoencoded Satellite Images https://arxiv.org/abs/2102.05692 3. Learning-Based Bias Correction for Time Difference of Arrival Ultra-Wideband Localization of Resource-Constrained Mobile Robots https://arxiv.org/abs/2103.01885 4. Sensing Via Collisions: A Smart Cage for Quadrotors with Applications to Self-Localization ## Robotics localization: 1. Improving Ranging-Based Location Estimation with Rigidity-Constrained CRLB-Based Motion Planning 2. Relative Position Estimation in Multi-Agent Systems Using Attitude-Coupled Range Measurements 3. Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching https://arxiv.org/abs/2103.03395 4. A Comparison between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction Tests https://arxiv.org/abs/2011.02508 5. State Estimation for Hybrid Wheeled-Legged Robots Performing Mobile Manipulation Tasks 6. Robust Localization for Planar Moving Robot in Changing Environment: A Perspective on Density of Correspondence and Depth https://arxiv.org/abs/2011.00439 ## PPA: 1. Weighted Node Mapping and Localisation on a Pixel Processor Array https://www.researchgate.net/publication/350187131_Weighted_Node_Mapping_and_Localisation_on_a_Pixel_Processor_Array/link/6054d443299bf17367550a00/download ## Sonar: 1. Predictive 3D Sonar Mapping of Underwater Environments Via Object-Specific Bayesian Inference https://arxiv.org/abs/2104.03203 ## Tactile SLAM: 1. Tactile SLAM: Real-Time Inference of Shape and Pose from Planar Pushing https://arxiv.org/abs/2011.07044 ## Active SLAM: 1. Invariant EKF Based 2D Active SLAM with Exploration Task ## IMU: 1. IMU Data Processing for Inertial Aided Navigation: A Recurrent Neural Network Based Approach https://arxiv.org/abs/2103.14286 2. Highly Efficient Line Segment Tracking with an IMU-KLT Prediction and a Convex Geometric Distance Minimization 3. IMU/Vehicle Calibration and Integrated Localization for Autonomous Driving 4. Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee https://arxiv.org/abs/2103.02357
gitextract_jirk81_h/ └── README.md
Condensed preview — 1 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (28K chars).
[
{
"path": "README.md",
"chars": 27825,
"preview": "# ICRA2021-SLAM-paper-list\n\nAll the classified papers can be download from Baidu cloud Disk:\nLink:https://pan.baidu.com/"
}
]
About this extraction
This page contains the full source code of the wanghuayou1028/ICRA2021-SLAM-paper-list GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 1 files (27.2 KB), approximately 7.3k tokens. 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.