Ros
Showing 36 of 253 projects
A ROS-based calibration tool for estimating extrinsic poses of lidar, radar, and camera sensor setups.
A ROS client library for connecting small embedded devices like Arduino to the Robot Operating System.
An Android app for visualizing and controlling ROS-based mobile robots via a customizable interface.
A ROS driver for u-blox GPS receivers, providing configuration, data parsing, and topic publishing for navigation solutions.
A robust system for multi-LiDAR extrinsic calibration, real-time odometry, and mapping without manual intervention.
A real-time visual odometry pipeline using stereo event-based cameras, leveraging Time Surfaces for direct geometric mapping and tracking.
A ROS driver for Livox LiDAR devices (Mid-40, Mid-70, Tele-15, Horizon, Avia) to publish point cloud data.
A ROS2 package for calibrating robot parameters like camera intrinsics, joint offsets, and frame transforms via optimization.
A modular ROS visualization tool with a plugin system focused on 2D data visualization.
An open-source ROS-based platform with practical exercises for learning robotics, AI, and computer vision.
A ROS-based object detection and pose estimation library for 2D and 3D applications using OpenCV.
An Unreal Engine plugin that enables communication with ROS (Robot Operating System) via rosbridge for robotics simulation.
A ROS wrapper for the AprilTag 3 visual fiducial detector, enabling marker-based pose estimation in robotics applications.
A GPU-accelerated C++ library for visual-inertial odometry frontend tasks, optimized for high-speed robotics.
A simple GUI application for editing ROS bag files by filtering topics, adjusting time ranges, and modifying transformations.
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 Node.js and TypeScript client library for ROS 2, enabling JavaScript development of robotics applications.
A curated list of open-source electronic modules, subsystems, and projects for building robots.
A Visual Studio Code extension providing comprehensive development support for Robot Operating System (ROS) 1 and ROS 2.
A ROS package that extracts line segments from LaserScan messages using a configurable split-and-merge algorithm with weighted line fitting.
A Qt Creator plugin that adds ROS-specific tools for managing Catkin workspaces, packages, and nodes within the IDE.
Open-source control module hardware and software for ROS-based robotics, designed for embedded systems.
A ROS library for LiDAR point cloud segmentation, enabling ground removal and object clustering for autonomous vehicle perception.
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
A generic framework for task planning and dispatch in ROS systems, encapsulating planning with common ROS library interfaces.
A graphical application for rapidly prototyping and deploying computer vision algorithms, primarily for robotics.
A ROS node that streams robot camera feeds and image topics over HTTP in multiple video formats for web browser viewing.
A CANopen driver framework for ROS enabling communication with industrial CANopen devices.
A web-based server that catalogs ROS bag files, provides search and download capabilities, and offers a REST API for automation.
A pure Go library for building ROS 1 client nodes, enabling lightweight cross-platform robotics and data streaming applications.
A ROS-based motion-primitives planner for fast and agile autonomous exploration with aerial robots.
A collection of ROS packages for advanced visualization tools and plugins for RViz and RQt.
A real-time ROS 2 package for detecting drivable roads and sidewalks from LIDAR point clouds in urban autonomous driving scenarios.
A full LiDAR SLAM system for static environment mapping using LiDAR with optional GPS, IMU, and odometry support.
Real-time Bayesian terrain traversability mapping and motion planning system for ROS-compatible unmanned ground vehicles using LiDAR point clouds.
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