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Using LiDAR sensory data as Input for Mapless Robot Navigation using Deep Reinforcement Learning
SC^2-PCR++: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration (TPAMI)
Elevation Mapping on GPU.
Using error-state Kalman filter to fuse the IMU and GPS data for localization.
ROS2 / FAST_LIO / PGO / Online Re-Localization / Consistent Map with BA or HBA
Minimal, robust, accurate and real-time LiDAR odometry
A toolbox for target-less LiDAR-camera calibration [ROS1/ROS2]
kitti2rosbag2 is designed to convert the KITTI Odometry dataset to ROS2 bag format.
A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis.
Implementations of a rather simple version of the Iterative Closest Point algorithm in various languages.
[ICRA2024] Official Repository for PeLiCal: Targetless Extrinsic Calibration via Penetrating Lines for RGB-D Cameras with Limited Co-visibility
🪙 COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry (ICRA 2024)
A collection of GICP-based fast point cloud registration algorithms
A large-scale multi-robot dataset for multi-robot SLAM
The dataset for the paper 'Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach'
Wild Visual Navigation: A system for fast traversability learning via pre-trained models and online self-supervision
The fuse stack provides a general architecture for performing sensor fusion live on a robot. Some possible applications include state estimation, localization, mapping, and calibration.
Probabilistic Motion Modeling Algorithm for Skid Steered Mobile Robots
Efficient and parallel algorithms for point cloud registration [C++, Python]
A Modular Optimization framework for Localization and mApping (MOLA)
ROS2 version of icp_localization
GNSS-IMU Localization based on Error-State Kalman Filter
Some examples to show how to use Quatro implemented in TEASER++ library
Official implementation: ICP-Flow: LiDAR Scene Flow Estimation with ICP (CVPR 2024).
Visual Inertial Odometry (VIO) / Simultaneous Localization & Mapping (SLAM) using iSAM2 framework from the GTSAM library.