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Flexible Spiking CPGs for Online Manipulation During Hexapod Walking

Neural signals for locomotion are influenced both by the neural network architecture and sensory inputs coordinating and adapting the gait to the environment. Adaptation relies on the ability to change amplitude, frequency, and phase of the signals within the sensorimotor loop in response to externa...

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Autores principales: Strohmer, Beck, Manoonpong, Poramate, Larsen, Leon Bonde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333644/
https://www.ncbi.nlm.nih.gov/pubmed/32676022
http://dx.doi.org/10.3389/fnbot.2020.00041
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author Strohmer, Beck
Manoonpong, Poramate
Larsen, Leon Bonde
author_facet Strohmer, Beck
Manoonpong, Poramate
Larsen, Leon Bonde
author_sort Strohmer, Beck
collection PubMed
description Neural signals for locomotion are influenced both by the neural network architecture and sensory inputs coordinating and adapting the gait to the environment. Adaptation relies on the ability to change amplitude, frequency, and phase of the signals within the sensorimotor loop in response to external stimuli. However, in order to experiment with closed-loop control, we first need a better understanding of the dynamics of the system and how adaptation works. Based on insights from biology, we developed a spiking neural network capable of continuously changing amplitude, frequency, and phase online. The resulting network is deployed on a hexapod robot in order to observe the walking behavior. The morphology and parameters of the network results in a tripod gait, demonstrating that a design without afferent feedback is sufficient to maintain a stable gait. This is comparable to results from biology showing that deafferented samples exhibit a tripod-like gait and adds to the evidence for a meaningful role of network topology in locomotion. Further, this work enables research into the role of sensory feedback and high-level control signals in the adaptation of gait types. A better understanding of the neural control of locomotion relates back to biology where it can provide evidence for theories that are currently not testable on live insects.
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spelling pubmed-73336442020-07-15 Flexible Spiking CPGs for Online Manipulation During Hexapod Walking Strohmer, Beck Manoonpong, Poramate Larsen, Leon Bonde Front Neurorobot Neuroscience Neural signals for locomotion are influenced both by the neural network architecture and sensory inputs coordinating and adapting the gait to the environment. Adaptation relies on the ability to change amplitude, frequency, and phase of the signals within the sensorimotor loop in response to external stimuli. However, in order to experiment with closed-loop control, we first need a better understanding of the dynamics of the system and how adaptation works. Based on insights from biology, we developed a spiking neural network capable of continuously changing amplitude, frequency, and phase online. The resulting network is deployed on a hexapod robot in order to observe the walking behavior. The morphology and parameters of the network results in a tripod gait, demonstrating that a design without afferent feedback is sufficient to maintain a stable gait. This is comparable to results from biology showing that deafferented samples exhibit a tripod-like gait and adds to the evidence for a meaningful role of network topology in locomotion. Further, this work enables research into the role of sensory feedback and high-level control signals in the adaptation of gait types. A better understanding of the neural control of locomotion relates back to biology where it can provide evidence for theories that are currently not testable on live insects. Frontiers Media S.A. 2020-06-26 /pmc/articles/PMC7333644/ /pubmed/32676022 http://dx.doi.org/10.3389/fnbot.2020.00041 Text en Copyright © 2020 Strohmer, Manoonpong and Larsen. 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
Strohmer, Beck
Manoonpong, Poramate
Larsen, Leon Bonde
Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title_full Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title_fullStr Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title_full_unstemmed Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title_short Flexible Spiking CPGs for Online Manipulation During Hexapod Walking
title_sort flexible spiking cpgs for online manipulation during hexapod walking
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333644/
https://www.ncbi.nlm.nih.gov/pubmed/32676022
http://dx.doi.org/10.3389/fnbot.2020.00041
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