Automating Collective Robotic System Design

Abstract

This paper presents a study on methods for body-brain (behavior-morphology) co-evolution in a collective evolutionary robotics system. We investigate a neuro-evolution developmental encoding method designed for the co-evolution of robot behavior-morphology couplings. This behavior-morphology evolution method is evaluated across increasingly complex (difficult) collective behavior task environments. This is in comparison to controller evolution within pre-engineered robot morphologies (sensory configurations). Task-complexity is equated with the degree of cooperation required in collective robotics tasks. Results indicate that the developmental method produces significantly more effective behavior-morphology couplings, compared to those evolved with direct encoding methods and controllers evolved within fixed morphologies. These results suggest that such developmental encoding methods could serve as a general evolutionary simulation design tool for automating collective robotic designs. An end goal is for such collective robotic system designs to be rapidly prototyped and deployed in the physical task environments for which they were evolved.