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A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion

Walking animals demonstrate impressive self-organized locomotion and adaptation to body property changes by skillfully manipulating their complicated and redundant musculoskeletal systems. Adaptive interlimb coordination plays a crucial role in this achievement. It has been identified that interlimb...

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Autores principales: Sun, Tao, Xiong, Xiaofeng, Dai, Zhendong, Owaki, Dai, Manoonpong, Poramate
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072274/
https://www.ncbi.nlm.nih.gov/pubmed/33912596
http://dx.doi.org/10.3389/frobt.2021.638684
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author Sun, Tao
Xiong, Xiaofeng
Dai, Zhendong
Owaki, Dai
Manoonpong, Poramate
author_facet Sun, Tao
Xiong, Xiaofeng
Dai, Zhendong
Owaki, Dai
Manoonpong, Poramate
author_sort Sun, Tao
collection PubMed
description Walking animals demonstrate impressive self-organized locomotion and adaptation to body property changes by skillfully manipulating their complicated and redundant musculoskeletal systems. Adaptive interlimb coordination plays a crucial role in this achievement. It has been identified that interlimb coordination is generated through dynamical interactions between the neural system, musculoskeletal system, and environment. Based on this principle, two classical interlimb coordination mechanisms (continuous phase modulation and phase resetting) have been proposed independently. These mechanisms use decoupled central pattern generators (CPGs) with sensory feedback, such as ground reaction forces (GRFs), to generate robot locomotion autonomously without predefining it (i.e., self-organized locomotion). A comparative study was conducted on the two mechanisms under decoupled CPG-based control implemented on a quadruped robot in simulation. Their characteristics were compared by observing their CPG phase convergence processes at different control parameter values. Additionally, the mechanisms were investigated when the robot faced various unexpected situations, such as noisy feedback, leg motor damage, and carrying a load. The comparative study reveals that the phase modulation and resetting mechanisms demonstrate satisfactory performance when they are subjected to symmetric and asymmetric GRF distributions, respectively. This work also suggests a strategy for the appropriate selection of adaptive interlimb coordination mechanisms under different conditions and for the optimal setting of their control parameter values to enhance their control performance.
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spelling pubmed-80722742021-04-27 A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion Sun, Tao Xiong, Xiaofeng Dai, Zhendong Owaki, Dai Manoonpong, Poramate Front Robot AI Robotics and AI Walking animals demonstrate impressive self-organized locomotion and adaptation to body property changes by skillfully manipulating their complicated and redundant musculoskeletal systems. Adaptive interlimb coordination plays a crucial role in this achievement. It has been identified that interlimb coordination is generated through dynamical interactions between the neural system, musculoskeletal system, and environment. Based on this principle, two classical interlimb coordination mechanisms (continuous phase modulation and phase resetting) have been proposed independently. These mechanisms use decoupled central pattern generators (CPGs) with sensory feedback, such as ground reaction forces (GRFs), to generate robot locomotion autonomously without predefining it (i.e., self-organized locomotion). A comparative study was conducted on the two mechanisms under decoupled CPG-based control implemented on a quadruped robot in simulation. Their characteristics were compared by observing their CPG phase convergence processes at different control parameter values. Additionally, the mechanisms were investigated when the robot faced various unexpected situations, such as noisy feedback, leg motor damage, and carrying a load. The comparative study reveals that the phase modulation and resetting mechanisms demonstrate satisfactory performance when they are subjected to symmetric and asymmetric GRF distributions, respectively. This work also suggests a strategy for the appropriate selection of adaptive interlimb coordination mechanisms under different conditions and for the optimal setting of their control parameter values to enhance their control performance. Frontiers Media S.A. 2021-04-12 /pmc/articles/PMC8072274/ /pubmed/33912596 http://dx.doi.org/10.3389/frobt.2021.638684 Text en Copyright © 2021 Sun, Xiong, Dai, Owaki and Manoonpong. https://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
Sun, Tao
Xiong, Xiaofeng
Dai, Zhendong
Owaki, Dai
Manoonpong, Poramate
A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title_full A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title_fullStr A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title_full_unstemmed A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title_short A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion
title_sort comparative study of adaptive interlimb coordination mechanisms for self-organized robot locomotion
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072274/
https://www.ncbi.nlm.nih.gov/pubmed/33912596
http://dx.doi.org/10.3389/frobt.2021.638684
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