On-Line Evolution of Controllers for Aggregating Swarm Robots in Changing Environments

Berend Weel, Mark Hoogendoorn, and A.E. Eiben

Abstract. One of the grand challenges in self-configurable robotics is to enable robots to change their configuration, autonomously, and in parallel, depending on changes in the environment. In this paper we investigate, in simulation, if this is possible through evolutionary algorithms (EA). To this end, we implement an unconventional on-line, on-board EA that works inside the robots, adapting their controllers to a given environment on-line. This adaptive robot swarm is then exposed to changing circumstances that require that robots aggregate into “organisms” or dis-aggregate into swarm mode again to improve their fitness. The experimental results clearly demonstrate that this EA is capable of adapting the system in real time, without human intervention.

LNCS 7492, p. 245 ff.

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