🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.
VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.
A Minimal Driver for Velodyne HDL-32E/64E VLP-16 Lidars
Efficient analysis of large datasets of point clouds recorded over time
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.
traversal row detection using UNet with LIDAR range images
Velodyne VLP16 point cloud organizer
A wrapper package for launch velodyne node for Velodyne 64E laser sensor
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