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

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

3D LIDAR-based Graph SLAM

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

ROS package to find a rigid-body transformation between a LiDAR and a camera for "LiDAR-Camera Calibration using 3D-3D Point correspondences"

:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.

loam code noted in Chinese（loam中文注解版）

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

Interactive Map Correction for 3D Graph SLAM

My awesome point cloud labeling tool

LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

Surfel-based Mapping for 3d Laser Range Data (SuMa)

Tutorial for using Kitti dataset easily

[ROS package] Lightweight and Accurate Point Cloud Clustering

VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.

Real-time people tracking using a 3D LIDAR

A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs

ROS/ROS2 enabled Sensor models (Assets) on Unity

L-CAS 3D Point Cloud Annotation Tool

Create 3D labelled bounding boxes in RViz

Easy description to run and evaluate Lego-LOAM with KITTI-data

This dataset is captured using a Velodyne VLP-16, which is mounted on an UGV - Clearpath Jackal, on Stevens Institute of Technology campus

A universal LiDAR and radar driver for ROS 2, supporting Hesai, Velodyne, Robosense and Continental sensors.

Robo Delivery Simulator

OpenDLV - A modern microservice-based software ecosystem powered by libcluon to make vehicles autonomous.

Code for Langer et al. "Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks", IROS, 2020.

Simulate Jackal with Velodyne VLP-16 or HDL-32E in Gazebo

VelodyneCapture is the general capture class to retrieve the laser data from Velodyne sensors using Boost.Asio and PCAP

LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".

Easy description to run and evaluate A-LOAM with KITTI-data