koide3

hdl_graph_slam. 3D LIDAR-based Graph SLAM

glim. GLIM: versatile and extensible point cloud-based 3D localization and mapping framework

fast_gicp. A collection of GICP-based fast point cloud registration algorithms

direct_visual_lidar_calibration. A toolbox for target-less LiDAR-camera calibration [ROS1/ROS2]

hdl_localization. Real-time 3D localization using a (velodyne) 3D LIDAR

small_gicp. Efficient and parallel algorithms for point cloud registration [C++, Python]

interactive_slam. Interactive Map Correction for 3D Graph SLAM

ndt_omp. Multi-threaded and SSE friendly NDT algorithm

iridescence. Visualization library for rapid prototyping of 3D algorithms [C++, Python]

gtsam_points. A collection of GTSAM factors and optimizers for point cloud SLAM

hdl_people_tracking. Real-time people tracking using a 3D LIDAR

hdl_global_localization. C++

slam_docker_collection. A collection of docker environments for 3D SLAM packages

monocular_person_following. Monocular camera-based person tracking and identification ROS framework for person following robots

livox_to_pointcloud2. C++

gazebo_apriltag. Apriltag models for gazebo

pointcloud_to_2dmap. C++

glim_ros2. C++

st_handeye_graph. General hand-eye calibration based on reprojection error minimization and pose graph optimization

glim_ext. C++

LeGO-LOAM-BOR. LeGO-LOAM-BOR: optimizer Lidar Odometry and Mapping

caratheodory2. C++

rviz_factor_graph_plugins. C++

automatic_tuning. C++

sparse_dynamic_calibration. Sparse and dynamic camera network calibration with visual odometry

glil_pubdoc. Public documentation for GLIL, A closed-source point-cloud-based real-time localization package

glim_ros1. C++

monocular_people_tracking. C++

cpp_parallel_code. Cuda

glim_mid360_tutorial.

points_inspector. An inspection tool for sensor_msgs/PointCloud2 messages [ROS1/ROS2]

open3d_graph_slam. Python

FAST_LIO_LOCALIZATION. A simple localization framework that can re-localize in built maps based on FAST-LIO.

ros2d2. A ROS package to make R2D2-like sound

ccf_person_identification. Convolutional Channel Features + Online boosting-based person identification for mobile robots

caratheodory. C++ implementation of the algorithm in "Fast and Accurate Least-Mean-Squares Solvers", NIPS19

pykalman_test. A simple UKF demo using pykalman

odometry_saver. C++

gtsam_docker. Dockerfile

setup_dds. Shell

slict. C++

scancontext. Global LiDAR descriptor for place recognition and long-term localization

mppi_playground. Model Predictive Path Integral Control (MPPI) with PyTorch

ccf_feature_extraction. Pretrained convolutional channel features for people identification

glim_extension_example. C++

vscode_ros.

direct_lidar_odometry. Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

amcl3d. Adaptive Monte Carlo Localization (AMCL) in 3D.

ppa. Shell

open_face_recognition. Python

LIO-SAM. LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

tf-pose-estimation. Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.

pcl. Point Cloud Library (PCL)

dial_controller. Python

sentech_gige_driver. C++

loam_velodyne. Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

Livox-SDK2. Drivers for receiving LiDAR data and controlling lidar, support Lidar HAP and Mid-360.

velodyne_packets2points.