[IROS'24] Globally localise your 2D LIDAR in a 2D map in no time
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Updated
Sep 28, 2024 - C++
[IROS'24] Globally localise your 2D LIDAR in a 2D map in no time
Efficient and parallel algorithms for point cloud registration [C++, Python]
Multi-threaded and SSE friendly NDT algorithm
A collection of GICP-based fast point cloud registration algorithms
Point cloud registration pipeline for robot localization and 3D perception
[IROS'22] Acquire robust odometry from your noisy panoramic 2D LIDAR
The Fourier Scan Matcher: a correspondenceless and closed-form matching algorithm for 2D panoramic LIDAR sensors
[ROS package] Lidar odometry from panoramic 2D range scans. Method: scan-matching without using correspondences, based on properties of the Discrete Fourier Transform
K-Closest Points and Maximum Clique Pruning for Efficient and Effective 3-D Laser Scan Matching (RA-L 2022)
An implementation of Simultaneous Localization and Mapping.
Laser scan matcher ported to ROS2
Implemented the Iterative Closest Point (ICP) algorithm, and used it to estimate the rigid transformation that optimally aligns two 3D point clouds
ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM
Simple 2D point-to-point scan matcher implemented in Python. Works with ROS1.
This repository contains solution for SLAM lectures taught by Claus Brenner on YouTube.
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