Showing 13 of 13 projects
A ROS2 wrapper for Intel RealSense cameras that provides depth, color, and IMU data as ROS topics and services.
A Python toolkit for working with the nuScenes and nuImages autonomous driving datasets, providing data loading, visualization, and evaluation utilities.
A target-less, automatic toolbox for LiDAR-camera extrinsic calibration that works with various sensor models without requiring calibration targets.
Fast and robust algorithm for segmenting Velodyne LiDAR point clouds into objects for autonomous driving applications.
A curated collection of papers, toolboxes, and notes for LiDAR-camera extrinsic calibration methods.
A modular ROS package for 3D/6D robot localization and point cloud registration using PCL, with dynamic map updates via OctoMap.
A multi-threaded, SSE-optimized Normal Distributions Transform algorithm for point cloud registration, offering up to 10x speedup over the original PCL implementation.
A ROS voxel layer using OpenVDB for efficient 3D environment representation with temporal decay, replacing voxel_grid for navigation.
A Siamese neural network for LiDAR-based loop closing and localization by predicting scan overlap and relative yaw angle.
A learning-based approach for moving object segmentation in 3D LiDAR data, distinguishing moving vs. static objects in real-time.
A real-time, uncertainty-aware deep learning model for semantic segmentation of 3D LiDAR point clouds in autonomous driving.
Legacy ROS2 drivers for Ouster OS-0, OS-1, and OS-2 lidars, providing sensor data processing and lifecycle management.
A curated collection of resources, datasets, and methods for 3D LiDAR-based Moving Object Segmentation (MOS) research.
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