Abstract
This paper presents experimental results of pattern (character and obstacle) recognition for controlling a mobile vehicle by adaptive resonance theory (ART) neural network. ART, a kind of competitive neural network, can self-organize and self-stabilize in response to complex input vectors. New memories are stored in such a fashion that existing ones are not forgotten of modified. The experiments are presented to show the ability of ART to control the mobile vehicle avoiding the obstacles. Finally, the experimental results and some future considerations are given.
