Robot shaping: developing autonomous agents through learning
Artificial Intelligence
Evolving 3d morphology and behavior by competition
Artificial Life
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In the vast majority of robotics experiments in which a controller is automatically optimized to produce some desired behavior, the robot's body plan does not change over the optimization process. This paper demonstrates the counterintuitive result that by gradually changing a quadrupedal robot's body plan from a prone to a standing posture over the course of the optimization process, desired behavior is discovered more rapidly compared to a simpler set up in which the same robot begins and maintains a standing posture throughout the optimization process. This mechanism of body plan change is referred to as morphological scaffolding, as the robot's body in effect scaffolds the optimization process. Moreover, it was found that this benefit becomes more pronounced for more challenging behaviors, and that this benefit is obtained only if the body plan gradually changes over the optimization process and during the evaluation of a single controller.