Implemented the Iterative Closest Point (ICP) algorithm, and used it to estimate the rigid transformation that optimally aligns two 3D point clouds
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Updated
Jun 24, 2023 - Python
Implemented the Iterative Closest Point (ICP) algorithm, and used it to estimate the rigid transformation that optimally aligns two 3D point clouds
An implementation of Simultaneous Localization and Mapping.
[ROS package] Lidar odometry from panoramic 2D range scans. Method: scan-matching without using correspondences, based on properties of the Discrete Fourier Transform
This repository contains solution for SLAM lectures taught by Claus Brenner on YouTube.
The Fourier Scan Matcher: a correspondenceless and closed-form matching algorithm for 2D panoramic LIDAR sensors
Localise your 2D LIDAR in a 2D map ex novo in no time
Simple 2D point-to-point scan matcher implemented in Python. Works with ROS1.
Acquire robust odometry from your noisy panoramic 2D LIDAR sensor
K-Closest Points and Maximum Clique Pruning for Efficient and Effective 3-D Laser Scan Matching (RA-L 2022)
ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM
Efficient and parallel algorithms for point cloud registration [C++, Python]
Laser scan matcher ported to ROS2
Point cloud registration pipeline for robot localization and 3D perception
A collection of GICP-based fast point cloud registration algorithms
Multi-threaded and SSE friendly NDT algorithm
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