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Dynamic primitives in the control of locomotion

Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We...

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Detalles Bibliográficos
Autores principales: Hogan, Neville, Sternad, Dagmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689288/
https://www.ncbi.nlm.nih.gov/pubmed/23801959
http://dx.doi.org/10.3389/fncom.2013.00071
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author Hogan, Neville
Sternad, Dagmar
author_facet Hogan, Neville
Sternad, Dagmar
author_sort Hogan, Neville
collection PubMed
description Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered.
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spelling pubmed-36892882013-06-25 Dynamic primitives in the control of locomotion Hogan, Neville Sternad, Dagmar Front Comput Neurosci Neuroscience Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered. Frontiers Media S.A. 2013-06-21 /pmc/articles/PMC3689288/ /pubmed/23801959 http://dx.doi.org/10.3389/fncom.2013.00071 Text en Copyright © 2013 Hogan and Sternad. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Neuroscience
Hogan, Neville
Sternad, Dagmar
Dynamic primitives in the control of locomotion
title Dynamic primitives in the control of locomotion
title_full Dynamic primitives in the control of locomotion
title_fullStr Dynamic primitives in the control of locomotion
title_full_unstemmed Dynamic primitives in the control of locomotion
title_short Dynamic primitives in the control of locomotion
title_sort dynamic primitives in the control of locomotion
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689288/
https://www.ncbi.nlm.nih.gov/pubmed/23801959
http://dx.doi.org/10.3389/fncom.2013.00071
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