Towards optimal sensor morphology for specific tasks: evolution of an artificial compound eye for estimating time to contact

For a systematic investigation of the interdependence between an agent's morphology and its task environment we constructed a system that is able to automatically generate optimal sensor morphologies for given tasks. The system consists of a robot with an artificial compound eye where the angular positions of the individual facets can be autonomously modified. This paper describes experiments on using artificial evolution to optimize the compound eye morphology for the task of estimating time to contact with obstacles. The resulting morphologies are in good agreement with the theoretically predicted optimal sensor density distribution for this task. By comparing our results with earlier experiments we find that our robot is able to evolve different optimal morphologies depending on the task required. Since the accuracy of our system proved to be good enough to easily distinguish qualitatively different optimal sensor morphologies we hope that also for more complex task environments it will allow us to identify the optimal sensor distribution with good precision.

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