High speed neural control for robot navigation

Abstract

This paper addresses the real time control of the Khepera mobile robot navigation in a maze with reflector walls. Boolean neural networks such as RAM and GSN models are applied to drive the vehicle, following a light source, while avoiding obstacles. Both neural networks are implemented with simple logic and arithmetic functions (NOT, AND, OR, Addition, and Comparison), aiming to improve the system speed. The results obtained are compared with two other control strategies: multilayer perceptron and fuzzy logic.