Development and research of chaotic mobile robot based on evolution system with GP

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In this study a new obstacle avoidance model based on fuzzy control is discussed. The membership function is a very importantfactor to raise the accuracy of fuzzy control. So, it proposes the method to create the membership function and make it more proper for the control. It can be created and tuned up in a systematic and autonomous way by applying evolution system of *netic programming(GP) that used the coupled chaotic system. The utility of method was examined by the computer *nulation and the real machine running experiment. The following were obtained. (1) The membership function can be created autonomously by easy learning for obstacle avoidance. (2) A series of functions needed can be generated contemporaneously to be applied to more complicated obstacle avoidance model. (3) It is possible to apply to the mounting robot.