Point Cloud
Showing 36 of 89 projects
A ROS-based method for extrinsic calibration between a 3D LiDAR and a 6-DOF pose sensor using point cloud crispness optimization.
A PyTorch framework for efficient 3D semantic and panoptic segmentation using superpoint-based transformer architectures.
An open-source 3D LIDAR-based mapping framework for semi-automatic, interactive correction of SLAM mapping failures.
A modular C++ and ROS 2 framework for building configurable LiDAR odometry and SLAM pipelines.
A multi-threaded, SSE-optimized Normal Distributions Transform algorithm for point cloud registration, offering up to 10x speedup over the original PCL implementation.
A curated list of research papers and resources for scene understanding in computer vision, covering 3D reconstruction, layout estimation, and primitive detection.
Convert KITTI autonomous driving datasets into ROS bag files for easy playback and integration.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
ROS packages for interfacing with Velodyne 3D LIDAR sensors in robotics applications.
A learning-based approach for moving object segmentation in 3D LiDAR data, distinguishing moving vs. static objects in real-time.
A ROS package for calibrating camera and LiDAR sensors using OpenCV's PnP and Levenberg-Marquardt optimization.
An airborne LiDAR point cloud ground filtering method based on cloth simulation for bare earth extraction.
A ROS-based tool for manually calibrating extrinsic parameters between Livox LiDAR sensors and cameras using board corners.
ROS 2 package for bidirectional conversion between 3D point clouds and 2D laser scans.
A fast and robust ground segmentation algorithm for 3D LiDAR point clouds, using concentric zone-based region-wise processing.
A data organization library for indexing and serving massive point cloud datasets losslessly.
A C++ implementation of the Go-ICP algorithm for globally optimal 3D point cloud registration with outlier trimming.
A single-stage 3D object detector for point clouds that improves localization precision by explicitly leveraging structure information.
A C++ library with Python bindings for reading, writing, and manipulating common animation particle formats like PDB, BGEO, and PTC.
A ROS driver for Livox LiDAR devices (Mid-40, Mid-70, Tele-15, Horizon, Avia) to publish point cloud data.
A real-time, uncertainty-aware deep learning model for semantic segmentation of 3D LiDAR point clouds in autonomous driving.
ROS & ROS2 implementation of Patchwork++, a fast and robust ground segmentation method for 3D LiDAR point clouds.
A 3D visualization library for ROS (Robot Operating System) in JavaScript, enabling web-based robot visualization.
A ROS 2 package for tightly-coupled LiDAR-inertial SLAM using NDT/GICP scan matching with loop closure.
A curated list of deep learning resources for 3D shape processing, covering classification, reconstruction, and generation.
A real-time ROS 2 package for detecting drivable roads and sidewalks from LIDAR point clouds in urban autonomous driving scenarios.
A simple, multi-language implementation of the Iterative Closest Point algorithm for 3D point cloud registration.
An open specification for streaming and distributing large volumes of 3D geographic data across web, mobile, and cloud platforms.
Real-time Bayesian terrain traversability mapping and motion planning system for ROS-compatible unmanned ground vehicles using LiDAR point clouds.
Real-time visualization and processing tool for live 3D LiDAR data from Velodyne sensors.
A Python library for converting ROS messages to and from NumPy arrays, enabling efficient data manipulation in robotics.
ROS 2 wrapper for Stereolabs ZED cameras, providing access to depth, point clouds, object detection, and spatial mapping.
A ROS driver for TI mmWave radar sensors with sensor fusion, multi-radar support, and camera overlay capabilities.
Real-time reception, recording, visualization, and processing of 3D LiDAR data from multiple manufacturers.
A Unity plugin for creating Lanelet2 vector maps for the Autoware autonomous driving platform.
Converts KITTI autonomous driving dataset raw data to ROS bags and provides a C++ library for direct data access.
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