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. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Trefzer, M. A., Kuyucu, T., Miller, J. F., & Tyrrell, A. M. (2010). Evolution and analysis of a robot controller based on a gene regulatory network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6274 LNCS, pp. 61–72). https://doi.org/10.1007/978-3-642-15323-5_6
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