An approach merging the concepts of fuzzy logic and sensor-based behaviors has been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The approach is implemented using custom-designed computer boards which include recently developed VLSI fuzzy inferencing chips. The design and operation of these boards are first described and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human- like navigation in a-priori unknown environments is discussed. The approach using superposition of elemental sensor-based behaviors expressed in the fizzy Sets theoretic framework is shown to allow easy development and testing of the inferencing rule base, while providing for progressive addition of behaviors to resolve situations of increasing complexity. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data.
['F.G. Pin', 'Hiroyuki Watanabe', 'James R. Symon', 'Robert S. Pattay']
Using Custom-designed Vlsi Fuzzy Inferencing Chips For The Autonomous Navigation Of A Mobile Robot