Evolution and Analysis of a Robot Controller Based on a Gene Regulatory Network

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.

• Type: Journal
• Year: 2010
• Where: ICES
• Authors: Martin Trefzer, Tüze Kuyucu, Julian F. Miller, Andy M. Tyrrell
• Keywords: Gene Regulatory Network, General Purpose Obstacle, Hardware, ICES 2010, Robot