This paper deals with the fuzzy drive control of an autonomous mobile robot. First, a fuzzy model (fuzzy expert system) for the human thought process is designed by using the idea of fuzziness, and secondly, it is applied to the autonomous mobile robot. The autonomous mobile robot is being investigated very actively in many research laboratories of companies and universities around the world. For example, there are the unmanned automated carrier in a factory, the working robot in extreme situations, and the house service robot [1, 3]. A human makes a proper decision and puts the decision into a proper action instantly under fuzzy and insufficient information. The fuzzy drive control system architecture is a hierarchy that is constructed by a visual sensor subsystem, a motor drive unit, and a fuzzy drive expert system which manages these subsystems. The visual sensor subsystem which perceives the outer environment such as the road, the obstacles, etc. is comprised of a TV camera and an image processing unit. The motor drive unit (motor controller) has the function of controlling the speed and the steering of the mobile robot by changing the revolution rate of motors mounted on the robot. The fuzzy drive expert system which is the core of the fuzzy drive control system recognizes the environment with the image data and sends control commands to the subsystems. By these commands from the drive expert system, each subsystem motivates the self-subsisting control function to achieve that purpose. This expert system has an inference unit and rules, such as recognition rules and control rules, which were obtained experimentally. As an application of the fuzzy drive control, experiments of driving an autonomous mobile robot on a straight road and one with corners are performed. From the experimental results, it was found that the robot control system has the faculty of flexibile circumstantial decision about equal to what a human is able to realize.
