There are 85 repositories under lidar topic.
A curated list of awesome data labeling tools
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
3D LIDAR-based Graph SLAM
GAAS is an open-source program designed for fully autonomous VTOL(a.k.a flying cars) and drones. GAAS stands for Generalized Autonomy Aviation System.
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
An Iterative Closest Point (ICP) library for 2D and 3D mapping in Robotics
ROS package to find a rigid-body transformation between a LiDAR and a camera for "LiDAR-Camera Calibration using 3D-3D Point correspondences"
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
loam code noted in Chinese(loam中文注解版)
Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving
😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.
DJI Onboard SDK Official Repository
SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)
🎓Automatically Update CV Papers Daily using Github Actions (Update Every 12th hours)
[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.
Interactive Map Correction for 3D Graph SLAM
Point cloud registration pipeline for robot localization and 3D perception
Real-time 3D localization using a (velodyne) 3D LIDAR
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.
LeGO-LOAM, LIO-SAM, LVI-SAM, FAST-LIO2, Faster-LIO, VoxelMap, R3LIVE, Point-LIO, KISS-ICP, DLO, DLIO, Ada-LIO, PV-LIO, SLAMesh, ImMesh, FAST-LIO-MULTI, M-LOAM, LOCUS, SLICT, MA-LIO application and comparison on Gazebo and real-world datasets. Installation and config files are provided.
VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking (CVPR 2023)
TypeScript/JavaScript 3D maps and geospatial data visualization engine library
A toolbox for target-less LiDAR-camera calibration [ROS1/ROS2]
Ground Segmentation from Lidar Point Clouds
OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)
Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22