Zheng, Chu and Li, Guanda and Hayashibe, Mitsuhiro (2022) Joint elasticity produces energy efficiency in underwater locomotion: Verification with deep reinforcement learning. Frontiers in Robotics and AI, 9. ISSN 2296-9144
pubmed-zip/versions/1/package-entries/frobt-09-957931/frobt-09-957931.pdf - Published Version
Download (3MB)
Abstract
Underwater snake robots have received attention because of their unique mechanics and locomotion patterns. Given their highly redundant degrees of freedom, designing an energy-efficient gait has been a main challenge for the long-term autonomy of underwater snake robots. We propose a gait design method for an underwater snake robot based on deep reinforcement learning and curriculum learning. For comparison, we consider the gait generated by a conventional parametric gait equation controller as the baseline. Furthermore, inspired by the joints of living organisms, we consider elasticity (stiffness) in the joints of the snake robot to verify whether it contributes to the generation of energy efficiency in the underwater gait. We first demonstrate that the deep reinforcement learning controller can produce a more energy-efficient gait than the gait equation controller in underwater locomotion, by finding the control patterns which maximize the effect of energy efficiency through the exploitation of joint elasticity. In addition, appropriate joint elasticity can increase the maximum velocity achievable by a snake robot. Finally, simulation results in different liquid environments confirm that the deep reinforcement learning controller is superior to the gait equation controller, and it can find adaptive energy-efficient motion even when the liquid environment is changed. The video can be viewed at https://youtu.be/wpwQihhntEY.
Item Type: | Article |
---|---|
Subjects: | Open Library Press > Mathematical Science |
Depositing User: | Unnamed user with email support@openlibrarypress.com |
Date Deposited: | 22 Jun 2023 06:05 |
Last Modified: | 19 Jun 2024 11:59 |
URI: | http://info.euro-archives.com/id/eprint/1696 |