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First-Order Dynamic Modeling and Control of Soft Robots
Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806042/ https://www.ncbi.nlm.nih.gov/pubmed/33501262 http://dx.doi.org/10.3389/frobt.2020.00095 |
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author | George Thuruthel, Thomas Renda, Federico Iida, Fumiya |
author_facet | George Thuruthel, Thomas Renda, Federico Iida, Fumiya |
author_sort | George Thuruthel, Thomas |
collection | PubMed |
description | Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing accuracy, efficiency and the natural dynamics. Controllers developed using second-order dynamic models tend to be computationally expensive, but allow optimal control. Here we propose that the dynamic model of a soft robot can be reduced to first-order dynamical equation owing to their high damping and low inertial properties, as typically observed in nature, with minimal loss in accuracy. This paper investigates the validity of this assumption and the advantages it provides to the modeling and control of soft robots. Our results demonstrate that this model approximation is a powerful tool for developing closed-loop task-space dynamic controllers for soft robots by simplifying the planning and sensory feedback process with minimal effects on the controller accuracy. |
format | Online Article Text |
id | pubmed-7806042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78060422021-01-25 First-Order Dynamic Modeling and Control of Soft Robots George Thuruthel, Thomas Renda, Federico Iida, Fumiya Front Robot AI Robotics and AI Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing accuracy, efficiency and the natural dynamics. Controllers developed using second-order dynamic models tend to be computationally expensive, but allow optimal control. Here we propose that the dynamic model of a soft robot can be reduced to first-order dynamical equation owing to their high damping and low inertial properties, as typically observed in nature, with minimal loss in accuracy. This paper investigates the validity of this assumption and the advantages it provides to the modeling and control of soft robots. Our results demonstrate that this model approximation is a powerful tool for developing closed-loop task-space dynamic controllers for soft robots by simplifying the planning and sensory feedback process with minimal effects on the controller accuracy. Frontiers Media S.A. 2020-07-21 /pmc/articles/PMC7806042/ /pubmed/33501262 http://dx.doi.org/10.3389/frobt.2020.00095 Text en Copyright © 2020 George Thuruthel, Renda and Iida. http://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 | Robotics and AI George Thuruthel, Thomas Renda, Federico Iida, Fumiya First-Order Dynamic Modeling and Control of Soft Robots |
title | First-Order Dynamic Modeling and Control of Soft Robots |
title_full | First-Order Dynamic Modeling and Control of Soft Robots |
title_fullStr | First-Order Dynamic Modeling and Control of Soft Robots |
title_full_unstemmed | First-Order Dynamic Modeling and Control of Soft Robots |
title_short | First-Order Dynamic Modeling and Control of Soft Robots |
title_sort | first-order dynamic modeling and control of soft robots |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806042/ https://www.ncbi.nlm.nih.gov/pubmed/33501262 http://dx.doi.org/10.3389/frobt.2020.00095 |
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