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Comparison of Modern Control Methods for Soft Robots

With the rise in new soft robotic applications, the control requirements increase. Therefore, precise control methods for soft robots are required. However, the dynamic control of soft robots, which is required for fast movements, is still an open topic and will be discussed here. In this contributi...

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Autores principales: Grube, Malte, Wieck, Jan Christian, Seifried, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737487/
https://www.ncbi.nlm.nih.gov/pubmed/36502166
http://dx.doi.org/10.3390/s22239464
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author Grube, Malte
Wieck, Jan Christian
Seifried, Robert
author_facet Grube, Malte
Wieck, Jan Christian
Seifried, Robert
author_sort Grube, Malte
collection PubMed
description With the rise in new soft robotic applications, the control requirements increase. Therefore, precise control methods for soft robots are required. However, the dynamic control of soft robots, which is required for fast movements, is still an open topic and will be discussed here. In this contribution, one kinematic and two dynamic control methods for soft robots are examined. Thereby, an LQI controller with gain scheduling, which is new to soft robotic applications, and an MPC controller are presented. The controllers are compared in a simulation regarding their accuracy and robustness. Additionally, the required implementation effort and computational effort is examined. For this purpose, the trajectory tracking control of a simple soft robot is studied for different trajectories. The soft robot is beam-shaped and tendon-actuated. It is modeled using the piecewise constant curvature model, which is one of the most popular modeling techniques in soft robotics. In this paper, it is shown that all three controllers are able to follow the examined trajectories. However, the dynamic controllers show much higher accuracy and robustness than the kinematic controller. Nevertheless, it should be noted that the implementation and computational effort for the dynamic controllers is significantly higher. Therefore, kinematic controllers should be used if movements are slow and small oscillations can be accepted, while dynamic controllers should be used for faster movements with higher accuracy or robustness requirements.
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spelling pubmed-97374872022-12-11 Comparison of Modern Control Methods for Soft Robots Grube, Malte Wieck, Jan Christian Seifried, Robert Sensors (Basel) Article With the rise in new soft robotic applications, the control requirements increase. Therefore, precise control methods for soft robots are required. However, the dynamic control of soft robots, which is required for fast movements, is still an open topic and will be discussed here. In this contribution, one kinematic and two dynamic control methods for soft robots are examined. Thereby, an LQI controller with gain scheduling, which is new to soft robotic applications, and an MPC controller are presented. The controllers are compared in a simulation regarding their accuracy and robustness. Additionally, the required implementation effort and computational effort is examined. For this purpose, the trajectory tracking control of a simple soft robot is studied for different trajectories. The soft robot is beam-shaped and tendon-actuated. It is modeled using the piecewise constant curvature model, which is one of the most popular modeling techniques in soft robotics. In this paper, it is shown that all three controllers are able to follow the examined trajectories. However, the dynamic controllers show much higher accuracy and robustness than the kinematic controller. Nevertheless, it should be noted that the implementation and computational effort for the dynamic controllers is significantly higher. Therefore, kinematic controllers should be used if movements are slow and small oscillations can be accepted, while dynamic controllers should be used for faster movements with higher accuracy or robustness requirements. MDPI 2022-12-03 /pmc/articles/PMC9737487/ /pubmed/36502166 http://dx.doi.org/10.3390/s22239464 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Grube, Malte
Wieck, Jan Christian
Seifried, Robert
Comparison of Modern Control Methods for Soft Robots
title Comparison of Modern Control Methods for Soft Robots
title_full Comparison of Modern Control Methods for Soft Robots
title_fullStr Comparison of Modern Control Methods for Soft Robots
title_full_unstemmed Comparison of Modern Control Methods for Soft Robots
title_short Comparison of Modern Control Methods for Soft Robots
title_sort comparison of modern control methods for soft robots
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737487/
https://www.ncbi.nlm.nih.gov/pubmed/36502166
http://dx.doi.org/10.3390/s22239464
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