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Twisting for soft intelligent autonomous robot in unstructured environments

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous loc...

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Detalles Bibliográficos
Autores principales: Zhao, Yao, Chi, Yinding, Hong, Yaoye, Li, Yanbin, Yang, Shu, Yin, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295757/
https://www.ncbi.nlm.nih.gov/pubmed/35605115
http://dx.doi.org/10.1073/pnas.2200265119
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author Zhao, Yao
Chi, Yinding
Hong, Yaoye
Li, Yanbin
Yang, Shu
Yin, Jie
author_facet Zhao, Yao
Chi, Yinding
Hong, Yaoye
Li, Yanbin
Yang, Shu
Yin, Jie
author_sort Zhao, Yao
collection PubMed
description Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.
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spelling pubmed-92957572022-11-23 Twisting for soft intelligent autonomous robot in unstructured environments Zhao, Yao Chi, Yinding Hong, Yaoye Li, Yanbin Yang, Shu Yin, Jie Proc Natl Acad Sci U S A Physical Sciences Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions. National Academy of Sciences 2022-05-23 2022-05-31 /pmc/articles/PMC9295757/ /pubmed/35605115 http://dx.doi.org/10.1073/pnas.2200265119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Physical Sciences
Zhao, Yao
Chi, Yinding
Hong, Yaoye
Li, Yanbin
Yang, Shu
Yin, Jie
Twisting for soft intelligent autonomous robot in unstructured environments
title Twisting for soft intelligent autonomous robot in unstructured environments
title_full Twisting for soft intelligent autonomous robot in unstructured environments
title_fullStr Twisting for soft intelligent autonomous robot in unstructured environments
title_full_unstemmed Twisting for soft intelligent autonomous robot in unstructured environments
title_short Twisting for soft intelligent autonomous robot in unstructured environments
title_sort twisting for soft intelligent autonomous robot in unstructured environments
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295757/
https://www.ncbi.nlm.nih.gov/pubmed/35605115
http://dx.doi.org/10.1073/pnas.2200265119
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