Automating the Incremental Evolution of Controllers for Physical Robots
Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
independently from simulation, that is, going from being, as Eiben et al. put it, “the evolution of things, rather than just the evolution of digital objects.…” The work presented here investigates how fully autonomous evolution of robot controllers can be realized in hardware, using an industrial robot and a marker-based computer vision system. In particular, this article presents an approach to automate the reconfiguration of the test environment and shows that it is possible, for the first time, to incrementally evolve a neural robot
controller for different obstacle avoidance tasks with no human intervention. Importantly, the system offers a high level of robustness and precision that could potentially open up the range of problems amenable to embodied evolution.