Ball Catching via 6R Manipulator

Project Overview

This project involves the development of control algorithms for a 6R robotic manipulator designed to catch a moving ball. The system integrates real-time motion planning to calculate the precise trajectory of the manipulator's arm and catch the ball in a simulated environment. The manipulator's control is implemented using ROS (Robot Operating System) and Gazebo, allowing for simulation and testing before real-world deployment.

Key Features

• Real-time motion planning for robotic arm control.
• Trajectory estimation and optimization to accurately predict and catch the ball.
• ROS and Gazebo integration for control and simulation.
• Control algorithms designed to enhance the accuracy and efficiency of the catching mechanism.

Tools Used

• ROS (Robot Operating System)
• Gazebo (Robotic Simulator)
• Python (Control algorithms and simulation management)
• C++ (ROS node development and motion planning)
• RViz (Visualization of robot movements)

Installation

To run this project on your local machine, follow these steps:

1. Set up ROS environment:

Ensure that you have ROS installed. This project was developed on ROS Noetic (Ubuntu 20.04). You can install ROS by following the official ROS installation guide.

2. Install Dependencies:

You will need to install Gazebo and other required ROS packages:

sudo apt-get install gazebo11 libgazebo11-dev
sudo apt-get install ros-noetic-ros-control ros-noetic-ros-controllers
sudo apt-get install ros-noetic-trajectory-msgs

3. Clone the repository:

Clone the repository to your workspace:

cd ~/catkin_ws/src
git clone https://github.com/kirankigi5/catkin_ws.git
cd ~/catkin_ws
catkin_make

4. Run the simulation:

Once everything is set up, you can run the Gazebo simulation with the following command:

roslaunch <your_package> <launch_file>.launch

Project Structure

• src/: Contains the ROS nodes for control algorithms and simulation setup.
• launch/: Contains ROS launch files to start various simulations.
• config/: Contains configuration files for robot parameters and controllers.
• urdf/: Contains the Unified Robot Description Format (URDF) files for the 6R manipulator model.
• scripts/: Contains Python scripts for control logic and simulation management.

How It Works

1. Trajectory Prediction: The ball's trajectory is predicted based on its current velocity and motion. The system uses control algorithms to compute the ideal position and orientation for the manipulator.

2. Motion Planning: Using ROS's MoveIt! and Gazebo, real-time motion planning is performed to calculate the required joint positions for the 6R manipulator to catch the ball.

3. Catching Mechanism: The manipulator adjusts its position to intercept the ball based on continuous feedback from sensors in the Gazebo simulation.

Future Work

• Implementing feedback from real-world sensors for a physical manipulator.
• Optimizing control algorithms for handling high-speed projectiles.
• Integrating machine learning-based prediction models for improved trajectory forecasting.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Special thanks to Prof. Spandan Roy for his guidance and support during this project.
• The robotics simulation environment was powered by ROS and Gazebo.