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A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation prob...
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/PMC7527605/ https://www.ncbi.nlm.nih.gov/pubmed/33041777 http://dx.doi.org/10.3389/fnbot.2020.00059 |
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author | Navarro-Alarcon, David Qi, Jiaming Zhu, Jihong Cherubini, Andrea |
author_facet | Navarro-Alarcon, David Qi, Jiaming Zhu, Jihong Cherubini, Andrea |
author_sort | Navarro-Alarcon, David |
collection | PubMed |
description | In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialize in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method. |
format | Online Article Text |
id | pubmed-7527605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75276052020-10-09 A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control Navarro-Alarcon, David Qi, Jiaming Zhu, Jihong Cherubini, Andrea Front Neurorobot Neuroscience In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialize in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method. Frontiers Media S.A. 2020-09-17 /pmc/articles/PMC7527605/ /pubmed/33041777 http://dx.doi.org/10.3389/fnbot.2020.00059 Text en Copyright © 2020 Navarro-Alarcon, Qi, Zhu and Cherubini. 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 | Neuroscience Navarro-Alarcon, David Qi, Jiaming Zhu, Jihong Cherubini, Andrea A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title | A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title_full | A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title_fullStr | A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title_full_unstemmed | A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title_short | A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control |
title_sort | lyapunov-stable adaptive method to approximate sensorimotor models for sensor-based control |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527605/ https://www.ncbi.nlm.nih.gov/pubmed/33041777 http://dx.doi.org/10.3389/fnbot.2020.00059 |
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