Evolution and analysis of a robot controller based on a gene regulatory network

Authors:
Martin A. Trefzer;Tüze Kuyucu;Julian F. Miller;Andy M. Tyrrell
Affiliations:
Department of Electronics, University of York, UK;Department of Electronics, University of York, UK;Department of Electronics, University of York, UK;Department of Electronics, University of York, UK
Venue:
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
Year:
2010

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Abstract

This paper explores the application of an artificial developmental system (ADS) to the field of evolutionary robotics by investigating the capability of a gene regulatory network (GRN) to specify a general purpose obstacle avoidance controller both in simulation and on a real robot. Experiments are carried out using the e-puck robot platform. It is further proposed to use cross-correlation between inputs and outputs in order to assess the quality of robot controllers more accurately than with observing its behaviour alone.