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
Simple 2D point-to-point scan matcher implemented in Python. Works with ROS1.
The Fourier Scan Matcher: a correspondenceless and closed-form matching algorithm for 2D panoramic LIDAR sensors
Acquire robust odometry from your noisy panoramic 2D LIDAR sensor
This repository contains solution for SLAM lectures taught by Claus Brenner on YouTube.
Localise your 2D LIDAR in a 2D map ex novo in no time
Laser scan matcher ported to ROS2
ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM
K-Closest Points and Maximum Clique Pruning for Efficient and Effective 3-D Laser Scan Matching (RA-L 2022)
Efficient and parallel algorithms for point cloud registration [C++, Python]
Multi-threaded and SSE friendly NDT algorithm
Point cloud registration pipeline for robot localization and 3D perception
A collection of GICP-based fast point cloud registration algorithms
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