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Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array
Surface texture information plays an important role in the cognition and manipulation of an object. Vision and touch are the two main methods for extracting an object’s surface texture information. However, vision is often limited since the viewing angle is uncertain during manipulation. In this art...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8951775/ https://www.ncbi.nlm.nih.gov/pubmed/35334732 http://dx.doi.org/10.3390/mi13030440 |
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author | Liu, Weiting Zhang, Guoshi Zhan, Binpeng Hu, Liang Liu, Tao |
author_facet | Liu, Weiting Zhang, Guoshi Zhan, Binpeng Hu, Liang Liu, Tao |
author_sort | Liu, Weiting |
collection | PubMed |
description | Surface texture information plays an important role in the cognition and manipulation of an object. Vision and touch are the two main methods for extracting an object’s surface texture information. However, vision is often limited since the viewing angle is uncertain during manipulation. In this article, we propose a fine surface texture detection method based on a stochastic resonance algorithm through a novel solid–liquid composite flexible tactile sensor array. A thin flexible layer and solid–liquid composite conduction structure on the sensor effectively reduce the attenuation of the contact force and enhance the sensitivity of the sensor. A series of ridge texture samples with different heights (0.9, 4, 10 μm), different widths (0.3, 0.5, 0.7, 1 mm), but the same spatial period (2 mm) of ridges were used in the experiment. The experimental results prove that the stochastic resonance algorithm can significantly improve the signal characteristic of the output signal of the sensor. The sensor has the capability to detect fine ridge texture information. The mean relative error of the estimation for the spatial period was 1.085%, and the ridge width and ridge height, respectively, have a monotonic mapping relationship with the corresponding model output parameters. The sensing capability to sense a fine texture of tactile senor surpasses the limit of human fingers. |
format | Online Article Text |
id | pubmed-8951775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89517752022-03-26 Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array Liu, Weiting Zhang, Guoshi Zhan, Binpeng Hu, Liang Liu, Tao Micromachines (Basel) Article Surface texture information plays an important role in the cognition and manipulation of an object. Vision and touch are the two main methods for extracting an object’s surface texture information. However, vision is often limited since the viewing angle is uncertain during manipulation. In this article, we propose a fine surface texture detection method based on a stochastic resonance algorithm through a novel solid–liquid composite flexible tactile sensor array. A thin flexible layer and solid–liquid composite conduction structure on the sensor effectively reduce the attenuation of the contact force and enhance the sensitivity of the sensor. A series of ridge texture samples with different heights (0.9, 4, 10 μm), different widths (0.3, 0.5, 0.7, 1 mm), but the same spatial period (2 mm) of ridges were used in the experiment. The experimental results prove that the stochastic resonance algorithm can significantly improve the signal characteristic of the output signal of the sensor. The sensor has the capability to detect fine ridge texture information. The mean relative error of the estimation for the spatial period was 1.085%, and the ridge width and ridge height, respectively, have a monotonic mapping relationship with the corresponding model output parameters. The sensing capability to sense a fine texture of tactile senor surpasses the limit of human fingers. MDPI 2022-03-14 /pmc/articles/PMC8951775/ /pubmed/35334732 http://dx.doi.org/10.3390/mi13030440 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Weiting Zhang, Guoshi Zhan, Binpeng Hu, Liang Liu, Tao Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title | Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title_full | Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title_fullStr | Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title_full_unstemmed | Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title_short | Fine Texture Detection Based on a Solid–Liquid Composite Flexible Tactile Sensor Array |
title_sort | fine texture detection based on a solid–liquid composite flexible tactile sensor array |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8951775/ https://www.ncbi.nlm.nih.gov/pubmed/35334732 http://dx.doi.org/10.3390/mi13030440 |
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