Real-time decision making for autonomous mobile robot using evolution strategy and anytime sensing

This paper presents a new real-time decision making method for an autonomous mobile robot based on an integration of evolutionary action search anal anytime sensing. The anytime sensing proposed in this paper increases a sensing information, which is necessary for the action search over the search time. With this property, it could be possible for the robot to search one of the ´good´ actions in less time because the computational amount increases step by step according to the increase of the sensing information by introducing the anytime sensing. As a result, we can make the search process faster in the time scale. We also analyze the proposed anytime sensing from viewpoint of Kullback-Leibler information criterion and show the usefulness through some simulation results