Evolutionary method for robot morphology: Case study of social robot Probo

Abstract

The appearance of robots is often made arbitrary as it relies more on guidelines than on a rigorous methodology. This paper presents a novel method of using genetic algorithms (GA) to improve the appearance of social robots with human feedback. Such general methods are interesting as they do not require prior artistic experience from the designer and can integrate the end-user in the loop. As a proof of concept, we carry out a case study by applying this method to the new design of the social robot Probo. Using designer feedback, the robot is evolved from its original design over five populations composed of 15 individuals. An online survey shows that the evolved designs are significantly improved compared to the original. These results indicate the feasibility of the method employed and gives rise to the possibility of non-technical end-users influencing the design of robot morphologies adapted for specific human-robot interaction requirements.