Fast and robust global registration for terrestrial robots @ ICRA2022
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Updated
May 27, 2024 - C++
Fast and robust global registration for terrestrial robots @ ICRA2022
C++ library and programs for reading and writing ASPRS LAS format with LiDAR data
Lidar Obstacle Detection
Configurable point cloud registration pipeline.
The project’s main goal is to investigate real-time object detection and tracking of pedestrians or bicyclists using a Velodyne LiDAR Sensor. Various point-cloud-based algorithms are implemented using the Open3d python package. The resulting 3D point cloud can then be processed to detect objects in the surrounding environment.
Cross-platform library to communicate with LiDAR devices of the Blickfeld GmbH.
LiDAR obstacle detection using Voxel Grids, RANSAC, Euclidean Clustering with Kd-Tree in C++ using PCL.
Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.
Tutorial for using Point Cloud Library (PCL) with ROS 2
Point Cloud 3D Visual Perception Simulation that runs on real LiDAR data
Object detector based on Point Cloud Library and Kinnect Camera
TreeScan3D is an innovative project that leverages the power of 3D computer vision and multi-threaded processing for efficient tree detection. Built using C++ and integrated with the Robot Operating System (ROS), this tool excels at accurately identifying trees in complex environments.
Multi Object Tracking Sensor Fusion 3D Interactive Simulation/Game in PCL
GLIDAR: a simple OpenGL LIDAR simulator
Point Cloud Library Tutorial with ROS
Sensor Fusion Nanodegree | Lidar Obstacle Detection in Autonomous Vehicles
A tool to subdivide point clouds into a set of smaller sub point clouds with user defined dimensions.
Plane Segmentation and Obstacle Clustering in LiDAR generated point clouds
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