Abstract
A fuzzy-neural realization of a behavior-based control system is described for a mobile robot by applying the soft-computing techniques, in which a simple fuzzy reasoning is assigned to one elemental behavior consisting of a single input-output relation, and then two consequent results from two behavioral groups are competed or cooperated. For the competition or cooperation between behavioral groups or elemental behaviors, a suppression unit is constructed as a neural network by using a sign function or saturation function. A Jacobian net is introduced to transform the results obtained from the competition or cooperation to those in the joint coordinate systems. Furthermore, we explain how to learn the present behavior-based control system by using a genetic algorithm. Finally, a simple terminal control problem is illustrated for a mobile robot with two independent driving wheels.
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Watanabe, K., Izumi, K. (1998). A Fuzzy-Neural Realization of Behavior-Based Control Systems for a Mobile Robot. In: Jain, L.C., Fukuda, T. (eds) Soft Computing for Intelligent Robotic Systems. Studies in Fuzziness and Soft Computing, vol 21. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1882-6_1
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DOI: https://doi.org/10.1007/978-3-7908-1882-6_1
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