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Controlling the Solo12 quadruped robot with deep reinforcement learning
Quadruped robots require robust and general locomotion skills to exploit their mobility potential in complex and challenging environments. In this work, we present an implementation of a robust end-to-end learning-based controller on the Solo12 quadruped. Our method is based on deep reinforcement le...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366154/ https://www.ncbi.nlm.nih.gov/pubmed/37488193 http://dx.doi.org/10.1038/s41598-023-38259-7 |
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author | Aractingi, Michel Léziart, Pierre-Alexandre Flayols, Thomas Perez, Julien Silander, Tomi Souères, Philippe |
author_facet | Aractingi, Michel Léziart, Pierre-Alexandre Flayols, Thomas Perez, Julien Silander, Tomi Souères, Philippe |
author_sort | Aractingi, Michel |
collection | PubMed |
description | Quadruped robots require robust and general locomotion skills to exploit their mobility potential in complex and challenging environments. In this work, we present an implementation of a robust end-to-end learning-based controller on the Solo12 quadruped. Our method is based on deep reinforcement learning of joint impedance references. The resulting control policies follow a commanded velocity reference while being efficient in its energy consumption and easy to deploy. We detail the learning procedure and method for transfer on the real robot. We show elaborate experiments. Finally, we present experimental results of the learned locomotion on various grounds indoors and outdoors. These results show that the Solo12 robot is a suitable open-source platform for research combining learning and control because of the easiness in transferring and deploying learned controllers. |
format | Online Article Text |
id | pubmed-10366154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103661542023-07-26 Controlling the Solo12 quadruped robot with deep reinforcement learning Aractingi, Michel Léziart, Pierre-Alexandre Flayols, Thomas Perez, Julien Silander, Tomi Souères, Philippe Sci Rep Article Quadruped robots require robust and general locomotion skills to exploit their mobility potential in complex and challenging environments. In this work, we present an implementation of a robust end-to-end learning-based controller on the Solo12 quadruped. Our method is based on deep reinforcement learning of joint impedance references. The resulting control policies follow a commanded velocity reference while being efficient in its energy consumption and easy to deploy. We detail the learning procedure and method for transfer on the real robot. We show elaborate experiments. Finally, we present experimental results of the learned locomotion on various grounds indoors and outdoors. These results show that the Solo12 robot is a suitable open-source platform for research combining learning and control because of the easiness in transferring and deploying learned controllers. Nature Publishing Group UK 2023-07-24 /pmc/articles/PMC10366154/ /pubmed/37488193 http://dx.doi.org/10.1038/s41598-023-38259-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Aractingi, Michel Léziart, Pierre-Alexandre Flayols, Thomas Perez, Julien Silander, Tomi Souères, Philippe Controlling the Solo12 quadruped robot with deep reinforcement learning |
title | Controlling the Solo12 quadruped robot with deep reinforcement learning |
title_full | Controlling the Solo12 quadruped robot with deep reinforcement learning |
title_fullStr | Controlling the Solo12 quadruped robot with deep reinforcement learning |
title_full_unstemmed | Controlling the Solo12 quadruped robot with deep reinforcement learning |
title_short | Controlling the Solo12 quadruped robot with deep reinforcement learning |
title_sort | controlling the solo12 quadruped robot with deep reinforcement learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366154/ https://www.ncbi.nlm.nih.gov/pubmed/37488193 http://dx.doi.org/10.1038/s41598-023-38259-7 |
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