LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
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Updated
Jun 15, 2024 - C++
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
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"
🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.
loam code noted in Chinese(loam中文注解版)
Interactive Map Correction for 3D Graph SLAM
Real-time 3D localization using a (velodyne) 3D LIDAR
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)
[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
L-CAS 3D Point Cloud Annotation Tool
A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs
Create 3D labelled bounding boxes in RViz
Easy description to run and evaluate Lego-LOAM with KITTI-data
Simulate Jackal with Velodyne VLP-16 or HDL-32E in Gazebo
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