Beacon-Guided Vehicle Model: Image Processing and MCU Implementation

This project involved developing a vehicle model guided by a beacon-based navigation system. The system utilizes a microcontroller (MCU) and camera module to detect and track beacons placed within a defined area. The vehicle model navigates the area by following the beacons, demonstrating a practical application of autonomous navigation.

The project involved the following stages:

Beacon Detection: The camera module captures images of the area, and image processing algorithms are applied to detect the beacon lights. The implemented image processing techniques include seed-based connected component search, median filtering, Gaussian filtering, and morphological matching. These algorithms effectively identify and isolate the beacon lights from the surrounding environment.
Navigation Control: The detected beacon locations are processed by the MCU, which controls the vehicle's movement based on the beacon's positions and the defined navigation logic.
Performance Evaluation: The navigation system's performance was evaluated based on the time taken for the vehicle to traverse the entire area and the accuracy of its navigation.

The project demonstrated the capabilities of combining MCU technology and image processing techniques to develop a functional and effective autonomous navigation system. This project highlights the potential of using these technologies for various applications, including robotics, autonomous vehicles, and industrial automation.