Abstract
In this paper, an application of neural networks and fuzzy rules for an autonomous mobile robot is described. The neural networks are used to select a suitable action from tracking and avoidance actions under operating environment and are adjusted by the back propagation algorithm so that the selected action corresponds to the action obtained by operator's decision skill. To realize the selected action, the steering angle and the speed are determined by using the fuzzy rules which are also automatically tuned so as to simulate the operator's control skill. Experimental results demonstrate the effectiveness of the proposed scheme for tracking and avoidance motions of the autonomous mobile robot.
