Vision-Based Autonomous Navigation System Using ANN and FSM Control

Autonomous mobile robot navigation is a very relevant problem in robotics research. This paper proposes a vision-based autonomous navigation system using artificial neural networks (ANN) and finite state machines (FSM). In the first step, ANNs are used to process the image frames taken from the robot´s camera, classifying the space, resulting in navigable or non-navigable areas (image road segmentation). Then, the ANN output is processed and used by a FSM, which identifies the robot´s current state, and define which action the robot should take according to the processed image frame. Different experiments were performed in order to validate and evaluate this approach, using a small mobile robot with integrated camera, in a structured indoor environment. The integration of ANN vision-based algorithms and robot´s action control based on a FSM, as proposed in this paper, demonstrated to be a promising approach to autonomous mobile robot navigation.