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Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots
Human beings can achieve a high level of motor performance that is still unmatched in robotic systems. These capabilities can be ascribed to two main enabling factors: (i) the physical proprieties of human musculoskeletal system, and (ii) the effectiveness of the control operated by the central nerv...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805700/ https://www.ncbi.nlm.nih.gov/pubmed/33501283 http://dx.doi.org/10.3389/frobt.2020.00117 |
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author | Angelini, Franco Della Santina, Cosimo Garabini, Manolo Bianchi, Matteo Bicchi, Antonio |
author_facet | Angelini, Franco Della Santina, Cosimo Garabini, Manolo Bianchi, Matteo Bicchi, Antonio |
author_sort | Angelini, Franco |
collection | PubMed |
description | Human beings can achieve a high level of motor performance that is still unmatched in robotic systems. These capabilities can be ascribed to two main enabling factors: (i) the physical proprieties of human musculoskeletal system, and (ii) the effectiveness of the control operated by the central nervous system. Regarding point (i), the introduction of compliant elements in the robotic structure can be regarded as an attempt to bridge the gap between the animal body and the robot one. Soft articulated robots aim at replicating the musculoskeletal characteristics of vertebrates. Yet, substantial advancements are still needed under a control point of view, to fully exploit the new possibilities provided by soft robotic bodies. This paper introduces a control framework that ensures natural movements in articulated soft robots, implementing specific functionalities of the human central nervous system, i.e., learning by repetition, after-effect on known and unknown trajectories, anticipatory behavior, its reactive re-planning, and state covariation in precise task execution. The control architecture we propose has a hierarchical structure composed of two levels. The low level deals with dynamic inversion and focuses on trajectory tracking problems. The high level manages the degree of freedom redundancy, and it allows to control the system through a reduced set of variables. The building blocks of this novel control architecture are well-rooted in the control theory, which can furnish an established vocabulary to describe the functional mechanisms underlying the motor control system. The proposed control architecture is validated through simulations and experiments on a bio-mimetic articulated soft robot. |
format | Online Article Text |
id | pubmed-7805700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78057002021-01-25 Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots Angelini, Franco Della Santina, Cosimo Garabini, Manolo Bianchi, Matteo Bicchi, Antonio Front Robot AI Robotics and AI Human beings can achieve a high level of motor performance that is still unmatched in robotic systems. These capabilities can be ascribed to two main enabling factors: (i) the physical proprieties of human musculoskeletal system, and (ii) the effectiveness of the control operated by the central nervous system. Regarding point (i), the introduction of compliant elements in the robotic structure can be regarded as an attempt to bridge the gap between the animal body and the robot one. Soft articulated robots aim at replicating the musculoskeletal characteristics of vertebrates. Yet, substantial advancements are still needed under a control point of view, to fully exploit the new possibilities provided by soft robotic bodies. This paper introduces a control framework that ensures natural movements in articulated soft robots, implementing specific functionalities of the human central nervous system, i.e., learning by repetition, after-effect on known and unknown trajectories, anticipatory behavior, its reactive re-planning, and state covariation in precise task execution. The control architecture we propose has a hierarchical structure composed of two levels. The low level deals with dynamic inversion and focuses on trajectory tracking problems. The high level manages the degree of freedom redundancy, and it allows to control the system through a reduced set of variables. The building blocks of this novel control architecture are well-rooted in the control theory, which can furnish an established vocabulary to describe the functional mechanisms underlying the motor control system. The proposed control architecture is validated through simulations and experiments on a bio-mimetic articulated soft robot. Frontiers Media S.A. 2020-09-11 /pmc/articles/PMC7805700/ /pubmed/33501283 http://dx.doi.org/10.3389/frobt.2020.00117 Text en Copyright © 2020 Angelini, Della Santina, Garabini, Bianchi and Bicchi. 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 Angelini, Franco Della Santina, Cosimo Garabini, Manolo Bianchi, Matteo Bicchi, Antonio Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title | Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title_full | Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title_fullStr | Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title_full_unstemmed | Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title_short | Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots |
title_sort | control architecture for human-like motion with applications to articulated soft robots |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805700/ https://www.ncbi.nlm.nih.gov/pubmed/33501283 http://dx.doi.org/10.3389/frobt.2020.00117 |
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