LINK: Target Detection and Tracking
This project presents a versatile robotic system framework for target tracking and obstacle avoidance. By leveraging YOLO (You Only Look Once) for real-time object detection, the system enables robots to identify, follow, and navigate around a target in dynamic environments.
Key Features:
- Real-Time Object Detection:
- Integrated YOLO model for detecting and tracking targets in the robot’s camera feed.
- Proportional and Proportional-Derivative Control:
- Includes both P-Control and PD-Control algorithms, allowing for responsive and stable target tracking.
- Obstacle Avoidance:
- Combines target following with obstacle avoidance using LIDAR data, ensuring smooth navigation.
Flexible Framework for Algorithm Testing:
This repository provides a robust platform for testing and experimenting with various target detection, tracking, and control algorithms. The modular design allows easy integration and evaluation of new algorithms, making it ideal for research and development in robotics.
This framework can be easily adapted for different models and use cases, making it a powerful tool for anyone working on robotic navigation, object tracking, or related applications.
I have used ROS Noetic for this because I was still working out the structure. I’m currently working on a more elaborate version of this framework based on ROS2. Just wanted to share this starter project for people into navigation and object following.
Cheers!
