Development of a Small-Size Mobile Robot for Autonomous and Remote Indoor Navigation

This project presents the design and implementation of a small-size mobile robot capable of indoor navigation, which can operate either autonomously or via manual control over a network. The robot’s compact size allows it to maneuver in tight spaces and narrow pathways inaccessible to humans. Equipped with a versatile camera system, the robot offers live video streaming with adjustable orientation, allowing the operator to explore its surroundings remotely. Autonomous navigation is achieved through graph theory-based pathfinding algorithms, augmented by artificial intelligence (AI) search methods and a predefined environmental map. The robot uses computer vision for landmark detection, enabling it to periodically recalibrate its position along its path and correct for sensor inaccuracies, improving its reliability over long distances. The project integrates a user-friendly graphical interface (GUI) and a manual controller box, which facilitates mode switching between autonomous and manual control and provides functionality to control the robot’s camera and flashlight. The system is built on the Robot Operating System (ROS), ensuring modularity and reuse of the developed software for other applications. The robot’s communication protocol is optimized for efficient interaction among various components, ensuring seamless operation. Future work will expand the system to include object detection, real-time mapping of unknown environments, and the integration of robotic arms for extended functionality, making the robot adaptable to a wide range of indoor tasks.