The evolution of an artificial compound eye by using adaptive hardware

Abstract

Object avoidance is a fundamental task of autonomous, mobile robots. For this task, the pertinent literature proposes various architectures, which vary from simple Braitenberg vehicles to camera-lens systems inspired by the compound eyes of insects. Due to certain hardware limitations, existing research resorts to prespecified sensor systems that remain fixed during all experiments and does modifications only in the software components of the controllers. By contrast, this paper is about the direct evolution of an artificial compound eye in hardware. The hardware consists of a particular robot that is able to autonomously modify the angular positions of 16 light sensors. Even though first experiments have been successful in evolving some solutions by means of evolutionary algorithms, they have also indicated that systematic comparisons between different evolutionary algorithms and codings schemes are required in order to speed up the evolutionary process. This paper summarizes some comparative simulation studies and validates their achievements on a physical robot. It turns out that these simulation studies can help to drastically improve the evolution of the eye's morphology with respect to both convergence speed and robustness if certain critical simulation parameters (e.g., noise level) are adopted from the physical robot.