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A robotic sensory system with high spatiotemporal resolution for texture recognition

Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Although modern robots integrated with flexible sensors can precisely detect pressure, shear force, and strain, they still perform insufficiently or require m...

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Autores principales: Bai, Ningning, Xue, Yiheng, Chen, Shuiqing, Shi, Lin, Shi, Junli, Zhang, Yuan, Hou, Xingyu, Cheng, Yu, Huang, Kaixi, Wang, Weidong, Zhang, Jin, Liu, Yuan, Guo, Chuan Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645869/
https://www.ncbi.nlm.nih.gov/pubmed/37963866
http://dx.doi.org/10.1038/s41467-023-42722-4
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author Bai, Ningning
Xue, Yiheng
Chen, Shuiqing
Shi, Lin
Shi, Junli
Zhang, Yuan
Hou, Xingyu
Cheng, Yu
Huang, Kaixi
Wang, Weidong
Zhang, Jin
Liu, Yuan
Guo, Chuan Fei
author_facet Bai, Ningning
Xue, Yiheng
Chen, Shuiqing
Shi, Lin
Shi, Junli
Zhang, Yuan
Hou, Xingyu
Cheng, Yu
Huang, Kaixi
Wang, Weidong
Zhang, Jin
Liu, Yuan
Guo, Chuan Fei
author_sort Bai, Ningning
collection PubMed
description Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Although modern robots integrated with flexible sensors can precisely detect pressure, shear force, and strain, they still perform insufficiently or require multi-sensors to respond to both static and high-frequency physical stimuli during the interaction. Here, we report a real-time artificial sensory system for high-accuracy texture recognition based on a single iontronic slip-sensor, and propose a criterion—spatiotemporal resolution, to corelate the sensing performance with recognition capability. The sensor can respond to both static and dynamic stimuli (0-400 Hz) with a high spatial resolution of 15 μm in spacing and 6 μm in height, together with a high-frequency resolution of 0.02 Hz at 400 Hz, enabling high-precision discrimination of fine surface features. The sensory system integrated on a prosthetic fingertip can identify 20 different commercial textiles with a 100.0% accuracy at a fixed sliding rate and a 98.9% accuracy at random sliding rates. The sensory system is expected to help achieve subtle tactile sensation for robotics and prosthetics, and further be applied to haptic-based virtual reality and beyond.
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spelling pubmed-106458692023-11-14 A robotic sensory system with high spatiotemporal resolution for texture recognition Bai, Ningning Xue, Yiheng Chen, Shuiqing Shi, Lin Shi, Junli Zhang, Yuan Hou, Xingyu Cheng, Yu Huang, Kaixi Wang, Weidong Zhang, Jin Liu, Yuan Guo, Chuan Fei Nat Commun Article Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Although modern robots integrated with flexible sensors can precisely detect pressure, shear force, and strain, they still perform insufficiently or require multi-sensors to respond to both static and high-frequency physical stimuli during the interaction. Here, we report a real-time artificial sensory system for high-accuracy texture recognition based on a single iontronic slip-sensor, and propose a criterion—spatiotemporal resolution, to corelate the sensing performance with recognition capability. The sensor can respond to both static and dynamic stimuli (0-400 Hz) with a high spatial resolution of 15 μm in spacing and 6 μm in height, together with a high-frequency resolution of 0.02 Hz at 400 Hz, enabling high-precision discrimination of fine surface features. The sensory system integrated on a prosthetic fingertip can identify 20 different commercial textiles with a 100.0% accuracy at a fixed sliding rate and a 98.9% accuracy at random sliding rates. The sensory system is expected to help achieve subtle tactile sensation for robotics and prosthetics, and further be applied to haptic-based virtual reality and beyond. Nature Publishing Group UK 2023-11-14 /pmc/articles/PMC10645869/ /pubmed/37963866 http://dx.doi.org/10.1038/s41467-023-42722-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Bai, Ningning
Xue, Yiheng
Chen, Shuiqing
Shi, Lin
Shi, Junli
Zhang, Yuan
Hou, Xingyu
Cheng, Yu
Huang, Kaixi
Wang, Weidong
Zhang, Jin
Liu, Yuan
Guo, Chuan Fei
A robotic sensory system with high spatiotemporal resolution for texture recognition
title A robotic sensory system with high spatiotemporal resolution for texture recognition
title_full A robotic sensory system with high spatiotemporal resolution for texture recognition
title_fullStr A robotic sensory system with high spatiotemporal resolution for texture recognition
title_full_unstemmed A robotic sensory system with high spatiotemporal resolution for texture recognition
title_short A robotic sensory system with high spatiotemporal resolution for texture recognition
title_sort robotic sensory system with high spatiotemporal resolution for texture recognition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645869/
https://www.ncbi.nlm.nih.gov/pubmed/37963866
http://dx.doi.org/10.1038/s41467-023-42722-4
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