Simultaneous design of morphology of body, neural systems and adaptability to environment of multi-link-type locomotive robots using genetic programming

Abstract

In this paper, morphology of body and neural systems that define the locomotion of multilinked locomotive robots that can adapt to changes in environment are designed using the evolutionary computation. The morphology of the body and neural systems have a close relationship to each other. The model of the robot is designed so that the morphology of the body and neural systems emerge simultaneously. The morphology of the body and neural systems are generated using a genetic programming. The tasks are that the robots move on ground including hills of different heights in the two dimensional lateral simulated world under the effect of gravity. The robots are evaluated based both on a moving distance and an efficiency. As a result, various combinations between the morphology of the body and neural systems of the robots were emerged. The evolved robots were able to go over hills which they had not experienced.