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Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity

As astronauts perform on-orbit servicing of extravehicular activity (EVA) without the help of the space station’s robotic arms, it will be rather difficult and labor-consuming to maintain the appropriate position in case of impact. In order to solve this problem, we propose the development of a wear...

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Autores principales: Zhao, Sikai, Zheng, Tianjiao, Sui, Dongbao, Zhao, Jie, Zhu, Yanhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975508/
https://www.ncbi.nlm.nih.gov/pubmed/36876304
http://dx.doi.org/10.3389/fnbot.2023.1093718
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author Zhao, Sikai
Zheng, Tianjiao
Sui, Dongbao
Zhao, Jie
Zhu, Yanhe
author_facet Zhao, Sikai
Zheng, Tianjiao
Sui, Dongbao
Zhao, Jie
Zhu, Yanhe
author_sort Zhao, Sikai
collection PubMed
description As astronauts perform on-orbit servicing of extravehicular activity (EVA) without the help of the space station’s robotic arms, it will be rather difficult and labor-consuming to maintain the appropriate position in case of impact. In order to solve this problem, we propose the development of a wearable robotic limb system for astronaut assistance and a variable damping control method for maintaining the astronaut’s position. The requirements of the astronaut’s impact-resisting ability during EVA were analyzed, including the capabilities of deviation resistance, fast return, oscillation resistance, and accurate return. To meet these needs, the system of the astronaut with robotic limbs was modeled and simplified. In combination with this simplified model and a reinforcement learning algorithm, a variable damping controller for the end of the robotic limb was obtained, which can regulate the dynamic performance of the robot end to resist oscillation after impact. A weightless simulation environment for the astronaut with robotic limbs was constructed. The simulation results demonstrate that the proposed method can meet the recommended requirements for maintaining an astronaut’s position during EVA. No matter how the damping coefficient was set, the fixed damping control method failed to meet all four requirements at the same time. In comparison to the fixed damping control method, the variable damping controller proposed in this paper fully satisfied all the impact-resisting requirements by itself. It could prevent excessive deviation from the original position and was able to achieve a fast return to the starting point. The maximum deviation displacement was reduced by 39.3% and the recovery time was cut by 17.7%. Besides, it also had the ability to prevent reciprocating oscillation and return to the original position accurately.
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spelling pubmed-99755082023-03-02 Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity Zhao, Sikai Zheng, Tianjiao Sui, Dongbao Zhao, Jie Zhu, Yanhe Front Neurorobot Neurorobotics As astronauts perform on-orbit servicing of extravehicular activity (EVA) without the help of the space station’s robotic arms, it will be rather difficult and labor-consuming to maintain the appropriate position in case of impact. In order to solve this problem, we propose the development of a wearable robotic limb system for astronaut assistance and a variable damping control method for maintaining the astronaut’s position. The requirements of the astronaut’s impact-resisting ability during EVA were analyzed, including the capabilities of deviation resistance, fast return, oscillation resistance, and accurate return. To meet these needs, the system of the astronaut with robotic limbs was modeled and simplified. In combination with this simplified model and a reinforcement learning algorithm, a variable damping controller for the end of the robotic limb was obtained, which can regulate the dynamic performance of the robot end to resist oscillation after impact. A weightless simulation environment for the astronaut with robotic limbs was constructed. The simulation results demonstrate that the proposed method can meet the recommended requirements for maintaining an astronaut’s position during EVA. No matter how the damping coefficient was set, the fixed damping control method failed to meet all four requirements at the same time. In comparison to the fixed damping control method, the variable damping controller proposed in this paper fully satisfied all the impact-resisting requirements by itself. It could prevent excessive deviation from the original position and was able to achieve a fast return to the starting point. The maximum deviation displacement was reduced by 39.3% and the recovery time was cut by 17.7%. Besides, it also had the ability to prevent reciprocating oscillation and return to the original position accurately. Frontiers Media S.A. 2023-02-15 /pmc/articles/PMC9975508/ /pubmed/36876304 http://dx.doi.org/10.3389/fnbot.2023.1093718 Text en Copyright © 2023 Zhao, Zheng, Sui, Zhao and Zhu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurorobotics
Zhao, Sikai
Zheng, Tianjiao
Sui, Dongbao
Zhao, Jie
Zhu, Yanhe
Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title_full Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title_fullStr Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title_full_unstemmed Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title_short Reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
title_sort reinforcement learning based variable damping control of wearable robotic limbs for maintaining astronaut pose during extravehicular activity
topic Neurorobotics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975508/
https://www.ncbi.nlm.nih.gov/pubmed/36876304
http://dx.doi.org/10.3389/fnbot.2023.1093718
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