We propose to make the physical characteristics of a robot oscillate while it learns to improve its behavioral performance. We consider quantities such as mass, actuator strength, and size that are usually fixed in a robot, and show that when those quantities oscillate at the beginning of the learning process on a simulated 2D soft robot, the performance on a locomotion task can be significantly improved. We investigate the dynamics of the phenomenon and conclude that in our case, surprisingly, a high-frequency oscillation with a large amplitude for a large portion of the learning duration leads to the highest performance benefits. Furthermore, we show that morphological wobbling significantly increases exploration of the search space.
@article{arxiv.2205.02811,
title = {Morphological Wobbling Can Help Robots Learn},
author = {Fabien C. Y. Benureau and Jun Tani},
journal= {arXiv preprint arXiv:2205.02811},
year = {2022}
}