Evolving Morphologies for Locomoting Micro-scale Robotic Agents

Abstract

Designing new locomotive mechanisms for micro-scale robotic systems could enable new approaches to tackling problems such as transporting cargos, or self-assembling in to pre-programmed architectures. Morphological factors often play a crucial role in determining the behaviour of microsystems, yet understanding how to design these aspects optimally is a challenge. This paper explores how the morphology of a multi-cellular micro-robotic agent can be optimised for reliable locomotion using artificial evolution in a stochastic simulator. Evolved morphologies are found to yield significantly better performance in terms of the reliability of the travel direction and the distance covered, compared to random morphologies.