Gregor Schoener
Centre de Recherche en Neruosciences Cognitives
Marseille, France
Using Attractor Dynamics to Generate Autonomous Robot Behavior
Generating simple motor behaviors in autonomous robots requires more than classical control. Simple forms of decision making are needed. The idea to use nonlinear attractor dynamics to achieve both stable behavior and decision making was originally motivated by analogies with nervous systems. The main ideas are reviewed and their implementation in a simple autonomous vehicle is illustrated. The method is compared to the potential field approach. The need for "neural" representation is identified and an outlook to problems of estimation and fusion is provided.