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Advanced implementation of LOAM
:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.
ICP algorithm , fast and easy to use in point cloud registration
Implementation of the Go-ICP algorithm for globally optimal 3D pointset registration
ROS graph slam for dynamic environment
3D LIDAR-based Graph SLAM
Real-time 3D localization using a (velodyne) 3D LIDAR
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
An "Iterative Closest Point" library for 2-D/3-D mapping in Robotics
LiDAR object detection based on RANSAC, k-d tree
A list of references on lidar point cloud processing for autonomous driving
Use pure lidar information to locate self.
3d lidar slam package.
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
loam SLAM with back and forth tilted scanning 2D laser, modified to work under ROS indigo and catkin
loam code noted in Chinese(loam中文注解版)
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
LOL: Lidar-only Odometry and Localization in 3D point cloud maps
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.
Multi-threaded and SSE friendly NDT algorithm
A list of point set matching/registration resources collected by Gang Wang
Track Advancement of SLAM 跟踪SLAM前沿动态【周更】
Robust Point Cloud Registration Using Iterative Probabilistic Data Associations ("Robust ICP")
A map representation based on 3D segments
Semantic Mapping using Surfel Mapping and Semantic Segmentation (Chen et al IROS 2019)
自动驾驶系统实现
Surfel-based Mapping for 3d Laser Range Data (SuMa)
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