This master's thesis presents a complete mobile robot navigation system, utilizing the A* algorithm for path planning and SLAM techniques for building a map of the environment. The system is based on the Raspberry Pi platform, which coordinates the operation of sensors such as the MPU-6050 gyroscope, motor encoders, and a distance sensor. Real-time data processing enables the robot to effectively avoid obstacles and navigate in dynamic environments.
The system offers flexibility and easy scalability. The Python-based program allows for the integration of additional features, while the grid map structure and A* algorithm ensure high precision in determining optimal routes. Moreover, the system supports communication via a graphical interface accessible through a web browser, simplifying interaction with the robot and enabling real-time monitoring of its status.
While the system functions as intended, there is potential for further optimization, particularly in terms of computational performance. Certain computations could be migrated to C++ to speed up the program's execution.
Verification tests conducted in real-world conditions confirmed the system's accuracy, with results indicating the possibility for further development towards more advanced robotic applications.
Here are some images showcasing the mobile robot navigation system in action:
