Development of a AI Robot Using ESP32-CAM for Object Detection and Autonomous Lane Tracking

"This project focuses on building an affordable AI-powered robot that combines object detection and autonomous lane tracking capabilities using the ESP32-CAM module. Designed with scalability and efficiency in mind, this project bridges artificial intelligence with embedded systems to create a practical, low-cost solution for educational and hobbyist applications in robotics and automation."
Project Overview and Goals:
AI-Powered Object Detection: Implement real-time object detection using pre-trained machine learning models to identify obstacles or targets in the robot’s environment.
Autonomous Lane Tracking: Develop an intelligent system for lane detection and navigation, enabling the robot to follow defined paths without human intervention.
Cost-Effective Design: Leverage the ESP32-CAM module’s processing power and affordability for efficient AI processing and camera-based vision.
Educational Value: Provide a comprehensive platform for understanding computer vision, AI integration, and robotics principles.
Key Components and Technologies:
ESP32-CAM Module: Serves as the robot’s main controller, equipped with Wi-Fi for remote monitoring and a camera for vision processing.
Machine Learning Models:
Use pre-trained models like MobileNet or YOLO for lightweight object detection.
Integrate OpenCV for lane detection through edge and contour detection techniques.
Motor Driver and Chassis: Control the robot’s movement with a compact motorized base, including servo motors for directional control.
Power Supply: Use a rechargeable battery to power the robot for extended autonomous operation.
Software Integration: Develop custom firmware using Arduino IDE or Python-based tools like MicroPython for programming and debugging.
Features and Benefits:
Real-Time Object Detection: Recognizes and avoids obstacles or tracks specific objects based on trained models.
Autonomous Lane Tracking: Follows lanes or predefined paths with precision, using vision-based algorithms for real-time adjustments.
Remote Monitoring: Offers control and feedback through a Wi-Fi connection, enabling real-time streaming and adjustments.
Cost Efficiency: Designed to be affordable without compromising functionality, making it ideal for beginners and students.
Learning Outcomes:
Understand the principles of computer vision and how to implement AI on embedded platforms.
Learn how to integrate cameras, sensors, and motor drivers with microcontrollers like the ESP32-CAM.
Explore object detection and lane tracking algorithms, including their adaptation for real-time applications.
Gain hands-on experience in developing low-cost robotics solutions with AI capabilities.
Applications:
Educational Robotics: Perfect for teaching robotics, AI, and IoT concepts.
Autonomous Vehicles: A simplified model to demonstrate navigation and decision-making principles.
Hobby Projects: A versatile platform for DIY robotics enthusiasts.
By completing this project, you will have developed a fully functional AI robot capable of performing object detection and lane tracking autonomously, demonstrating a practical understanding of AI, computer vision, and embedded systems at a low cost.