Fuzzy control of a behavior-based mobile robot

In this paper, a fuzzy controller is developed for of an autonomous nonholonomic mobile robot, which was successfully built with behavior-based artificial intelligence that is implemented by several levels of competences and behaviors. The Lyapunov's direct method is used to formulate a class of control laws that guarantee the convergence of the steering errors to zero. Certain constraints for the control laws are presented for the selection of a suitable rule base for the fuzzy controller, which makes the system asymptotically stable. The stability of the proposed fuzzy controller is proved theoretically and demonstrated by simulation studies. Experiments are also conducted to investigate the performance of the developed fuzzy controller.