LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
- lidar-odometry
- lidar-slam
- loam-velodyne
- lidar-inertial
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LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Webots Robot Simulator
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles
An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.
A LiDAR odometry pipeline that just works
3D LIDAR-based Graph SLAM
Index repo for Kimera code
An Iterative Closest Point (ICP) library for 2D and 3D mapping in Robotics
Build your own robot duck. XGO-Duck is a 3D-printable biped powered by Arduino UNO Q and 15 servos, adapted from Pollen Robotics' Microduck. Includes mechanical models, PCB designs, a BOM, and an assembly guide. Build it, explore its motion, and make it your own.
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
gradslam is an open source differentiable dense SLAM library for PyTorch
A map representation based on 3D segments
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
LLM-first, 3D-native robotics and simulation workspace.
SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)
Interactive Map Correction for 3D Graph SLAM
Point cloud registration pipeline for robot localization and 3D perception
CubeSLAM: Monocular 3D Object Detection and SLAM
A new voxel layer leveraging modern 3D graphics tools to modernize navigation environmental representations
Real-Time 3D Semantic Reconstruction from 2D data
OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)
Real time semantic slam in ROS with a hand held RGB-D camera
A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.