APF_PTC

This repository contains an implementation of Artificial Potential Field (APF) for path planning and a PID controller for target tracking in robotics. The project aims to demonstrate obstacle avoidance and precise movement control for autonomous navigation.

Features

• Artificial Potential Field Algorithm: Used for path planning to guide robots towards a target while avoiding obstacles.
• PID Controller: Ensures accurate path tracking and stability.
• Multilingual Implementation: C++ and Python scripts for flexibility.

File Structure

• apft_05.cpp and similar: C++ implementations of the APF path planning.
• apftc_c.py: Python script for controller-based navigation.
• apftc_pid_01.cpp: Combines path planning with PID control.
• test1.py: Example for testing purposes.

Dependencies

• Standard C++11 or higher compiler
• Python 3.x
• Libraries: matplotlib (for Python visualization)

How to Use

1. Compile the C++ files using:

   g++ apftc_pid_01.cpp -o apf_pid -std=c++11
   ./apf_pid
   

2. Run the Python script:

   python3 apftc_c.py
   

Future Enhancements

• Integration with ROS for real-world robotics applications.
• Dynamic obstacle handling.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.

License

This project is licensed under the MIT License.

Contact

For inquiries, reach out to the repository owner on GitHub.