Abstract
In this paper, we perform experiments that autonomous mobile robot controllers are developed in by the integrative optimization system. Autonomous mobile robot controllers are developed using meta-heuristics, if the behavior of robot is able to evaluate. However, in an actual environment, it is difficult to develop the robot controller using meta-heuristics because meta-heuristics requires large numbers of function evaluations. And large numbers of function evaluations have problems which are to increase experimental time and the maintenance cost. The integrative optimization system is a method to improve these problems. A general integrative optimization system constructs an approximate response surface by the Radial Basis Function network and optimizes to the approximate response surface by the optimization method. Through experiments in a simulator and actual environment, the authors show that it is an effective method to develop the autonomous mobile robot controller by the integrative optimization system.
