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UR3 Berry Harvesting Integration

This repository showcases the integration of various technologies, including the UR3 robotic arm, Intel D435F camera, custom-made gripper, and other components for berry harvesting applications. The goal of this project is to develop a robust system that can detect berries, determine their pose, and execute precise gripping and harvesting actions using the UR3 arm.

🔧 Technologies Used

The integration project utilizes the following technologies:

  • ROS (Robot Operating System) - Noetic version
  • RViz - 3D visualization tool for ROS
  • RQt - GUI framework for ROS
  • ddynamic_reconfigure - Dynamic reconfiguration for ROS
  • realsense-ros - ROS packages for Intel RealSense cameras
  • aruco_ros - ROS wrapper for ArUco markers

📁 Project Structure

The workspace structure for the UR3 Berry Harvesting Integration project is as follows:

cam_ws/
├── build/
├── devel/
└── src/
│ ├── aruco_ros/
│ ├── realsense-ros/
│ ├── ddynamic_reconfigure/
└── ...

  • ur3_ws: This workspace contains the UR3-specific packages and dependencies required for the robotic arm integration. It includes packages like universal_robots_ros_driver and universal_robot.

  • cam_ws: This workspace focuses on camera-related packages and dependencies. It includes packages like realsense-ros and ddynamic_reconfigure.

🚀 Getting Started

To start the integration system, follow these steps:

  1. Launch the camera:
roslaunch realsense2_camera rs_camera.launch
  1. Launch the aruco_ros node to detect the identifiable objects:
roslaunch aruco_ros single.launch
  1. Launch the RViz visualization tool using the example_rviz.launch file:
roslaunch ur_robot_driver example_rviz.launch
  1. Start the UR3 robot using the ur3_bringup.launch file:
roslaunch ur_robot_driver ur3_bringup.launch robot_ip:=<YOUR_ROBOT_IP>
  1. Run the real_controller_examples.py script to control the vision system, calculate the pose, and execute other relevant actions:
rosrun ur_control real_controller_examples.py

Ensure that you have correctly configured the IP address of your UR3 robot in the launch file.

🐳 Dockerfile

To simplify the setup process, a Dockerfile is provided in the repository. The Dockerfile sets up the necessary environment and installs the required ROS packages and dependencies. It can be used to create a Docker image that encapsulates the entire project's workspace.

🙏 Acknowledgements

This project acknowledges the valuable resources and guidance provided by the following tools and repositories:

For more information on how to integrate the UR3 arm with the camera system and perform berry harvesting tasks, please refer to the provided scripts and documentation in the repository.

📧 Contact Information

For any questions or further inquiries, please feel free to contact me at [email protected].

📃 License

This project is licensed under the terms of the MIT License. Feel free to use, modify, and distribute the code, keeping in mind the attribution and licensing requirements.