Combining reactive behaviors using a hierarchy of fuzzy controllers

Abstract

Realizing complex robotic tasks by combining elementary behaviors is simple, robust and effective. Learning controllers from examples avoids manual identification of system states and actions and direct definition of their relationships. Fuzzy controllers represent direct associations between input and output variables, typical of reactive behaviors, in a form understandable by both automatic tools and humans. The paper describes the application of a set of tools developed for supporting the automatic design of fuzzy controllers (recording of associations between control commands and system states, identification of the required controller's components). Safe navigation of a real vehicle in an unknown indoor environment is addressed by combining two behaviors, wall-following and door-crossing, using a third module for judging their competence in each situation. Its performance, driving a Scout in our offices, is shown and related to the limitations of the two basic controllers.