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UR5 Pick-and-Place Simulation with ROS2 & Gazebo

This repository contains packages for simulating a UR5 robotic arm using ROS2 and Gazebo. The project focuses on performing pick-and-place tasks on a red cube identified by an AprilTag, using an onboard camera for detection and localization.

While the project is still a work in progress and not all components are fully implemented, it showcases my work in robotics simulation, perception, and control. Because it is a complex projects, all files are not present in here.

I advise you to build your proper ROS2 configuration with your different packages and then get some elements of this reposotiroy to get some ideas if you have a simular project

Project Overview

  • Robot: UR5 robotic arm, simulated in Gazebo.

  • Perception: Detection of a red cube using AprilTags with an onboard camera.

  • Control: Pick-and-place tasks implemented via ROS2 nodes controlling the UR5 arm.

  • Mathematics & Algorithms:

    • Quaternions for orientation handling.
    • SVD (Singular Value Decomposition) used in pose estimation and coordinate transformations.
  • Simulation: All interactions are performed in Gazebo, providing a realistic physics environment.

The archive includes the ROS2 packages I developed, which contain nodes, launch files, and scripts required to perform the simulation tasks mentioned above.

You can find a global presentation of the project here : presentation of the project

Archive Contents

Notes

  • This project was primarily a learning and experimental effort to explore:

    • Robotics simulation workflows in ROS2 and Gazebo
    • Integration of computer vision (AprilTag detection) for robotic manipulation
    • Handling robot kinematics and orientation using quaternions
  • Some aspects of the full pick-and-place workflow may not be fully completed.

  • The code is structured to allow further development and experimentation.

Technologies Used

  • ROS2 – Robot Operating System 2 for communication and control.
  • Gazebo – 3D robotics simulator for realistic physics interactions.
  • AprilTag – Visual fiducial markers for object detection.
  • Python & C++ – Nodes for perception and control.
  • Quaternions & SVD – Mathematical tools for orientation and pose estimation.

This project demonstrates practical experience in robotic simulation, perception, and control using ROS2 and provides a foundation for extending pick-and-place tasks to more complex scenarios.

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Simulation of a UR5 robotic arm using ROS2 and Gazebo, performing pick-and-place tasks on a red cube with an AprilTag, using an onboard camera for detection and localization.

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