Automatic generation of fuzzy sensorimotor rules for mobile robotics

We briefly compare world modelling (or map-building) and reactive behavior as techniques for mobile robot controller design. We then describe an approach to automatic generation of behavioral rules for a mobile robot which attempts to combine the best features of these two techniques. It is composed of three parts. In map-building mode the robot forms a “fuzzy image” of a maze in terms of the location of obstacles and goal states. It then acts as a “teacher”, providing examples of trajectories from which may be extracted generalised behavioral rules through a process of fuzzy clustering of the trajectory data. These rules are then used in a fuzzy controller for the agent. Finally we present our first results from implementing this composite architecture in simulation