Learning in a Fuzzy Logic Robot Controller

Abstract

Although Zadeh defined the basic operations of fuzzy set theory over thirty years ago (Zadeh, 1965), fuzzy logicbased controllers have just recently become the technique of choice for many researchers in robotics. Fuzzy logic controllers allow for the integration of high-level, humandesigned plans to operate along side immediate, reactive actions in a successful manner. The key to this line of research has been the development of the concept of behaviors. Behaviors as a method of controlling robots were inspired by Brooks ’ subsumption architecture (Brooks, 1986). Generally, a behavior is a simple, focused, perceptual trigger and associated action. An example might look like: IF obstacle-on-right THEN turn-left. The obstacle-on-right is the perceptual trigger that