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The Case for Engineering the Evolution of Robot Controllers

In this paper, we discuss how the combination of evolutionary techniques and engineering-oriented approaches is an effective methodology for leveraging the potential of evolutionary robotics (ER) in the synthesis of behavioural control. We argue that such combination can eliminate the issues that have prevented ER from scaling to complex real-world tasks, namely: (i) the bootstrap problem, (ii) deception, (iii) the reality gap effect, and (iv) the prohibitive amount of time necessary to evolve controllers directly in real robotic hardware. We present recent studies carried out in our research group involving real-robot and simulation-based experiments. We provide examples of how the synergistic effects of evolution and engineering overcome each other’s limitations and significantly extend their respective capabilities, thereby opening a new path in the design of robot controllers.