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A soft artificial muscle driven robot with reinforcement learning
Soft robots driven by stimuli-responsive materials have their own unique advantages over traditional rigid robots such as large actuation, light weight, good flexibility and biocompatibility. However, the large actuation of soft robots inherently co-exists with difficulty in control with high precis...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162322/ https://www.ncbi.nlm.nih.gov/pubmed/30266999 http://dx.doi.org/10.1038/s41598-018-32757-9 |
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author | Yang, Tao Xiao, Youhua Zhang, Zhen Liang, Yiming Li, Guorui Zhang, Mingqi Li, Shijian Wong, Tuck-Whye Wang, Yong Li, Tiefeng Huang, Zhilong |
author_facet | Yang, Tao Xiao, Youhua Zhang, Zhen Liang, Yiming Li, Guorui Zhang, Mingqi Li, Shijian Wong, Tuck-Whye Wang, Yong Li, Tiefeng Huang, Zhilong |
author_sort | Yang, Tao |
collection | PubMed |
description | Soft robots driven by stimuli-responsive materials have their own unique advantages over traditional rigid robots such as large actuation, light weight, good flexibility and biocompatibility. However, the large actuation of soft robots inherently co-exists with difficulty in control with high precision. This article presents a soft artificial muscle driven robot mimicking cuttlefish with a fully integrated on-board system including power supply and wireless communication system. Without any motors, the movements of the cuttlefish robot are solely actuated by dielectric elastomer which exhibits muscle-like properties including large deformation and high energy density. Reinforcement learning is used to optimize the control strategy of the cuttlefish robot instead of manual adjustment. From scratch, the swimming speed of the robot is enhanced by 91% with reinforcement learning, reaching to 21 mm/s (0.38 body length per second). The design principle behind the structure and the control of the robot can be potentially useful in guiding device designs for demanding applications such as flexible devices and soft robots. |
format | Online Article Text |
id | pubmed-6162322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61623222018-10-02 A soft artificial muscle driven robot with reinforcement learning Yang, Tao Xiao, Youhua Zhang, Zhen Liang, Yiming Li, Guorui Zhang, Mingqi Li, Shijian Wong, Tuck-Whye Wang, Yong Li, Tiefeng Huang, Zhilong Sci Rep Article Soft robots driven by stimuli-responsive materials have their own unique advantages over traditional rigid robots such as large actuation, light weight, good flexibility and biocompatibility. However, the large actuation of soft robots inherently co-exists with difficulty in control with high precision. This article presents a soft artificial muscle driven robot mimicking cuttlefish with a fully integrated on-board system including power supply and wireless communication system. Without any motors, the movements of the cuttlefish robot are solely actuated by dielectric elastomer which exhibits muscle-like properties including large deformation and high energy density. Reinforcement learning is used to optimize the control strategy of the cuttlefish robot instead of manual adjustment. From scratch, the swimming speed of the robot is enhanced by 91% with reinforcement learning, reaching to 21 mm/s (0.38 body length per second). The design principle behind the structure and the control of the robot can be potentially useful in guiding device designs for demanding applications such as flexible devices and soft robots. Nature Publishing Group UK 2018-09-28 /pmc/articles/PMC6162322/ /pubmed/30266999 http://dx.doi.org/10.1038/s41598-018-32757-9 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yang, Tao Xiao, Youhua Zhang, Zhen Liang, Yiming Li, Guorui Zhang, Mingqi Li, Shijian Wong, Tuck-Whye Wang, Yong Li, Tiefeng Huang, Zhilong A soft artificial muscle driven robot with reinforcement learning |
title | A soft artificial muscle driven robot with reinforcement learning |
title_full | A soft artificial muscle driven robot with reinforcement learning |
title_fullStr | A soft artificial muscle driven robot with reinforcement learning |
title_full_unstemmed | A soft artificial muscle driven robot with reinforcement learning |
title_short | A soft artificial muscle driven robot with reinforcement learning |
title_sort | soft artificial muscle driven robot with reinforcement learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162322/ https://www.ncbi.nlm.nih.gov/pubmed/30266999 http://dx.doi.org/10.1038/s41598-018-32757-9 |
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