Evolutionary Design of Mobile Robot Behaviors for Action-Based Environment Modeling

Abstract. This paper describes an evolutionary way to design behaviors of a mobile robot for recognizing environments. We have proposed an action-based approach (called AEM) for a mobile robot to recognize environments. In AEM, a behavior-based mobile robot acts in each environments and action sequences are obtained. The action sequences are transformed into vectors characterizing the environments, and the robot identifies the environments with the vectors. The design of suitable behaviors for AEM is very difficult for human because the search space is huge and intuitive understanding is hard. Thus we develop the evolutionary design of such behaviors using genetic algorithm.