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A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network
Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially d...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339246/ https://www.ncbi.nlm.nih.gov/pubmed/30577675 http://dx.doi.org/10.3390/s19010027 |
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author | Zhang, Youzhi Ye, Jinhua Lin, Zhengkang Huang, Shuheng Wang, Haomiao Wu, Haibin |
author_facet | Zhang, Youzhi Ye, Jinhua Lin, Zhengkang Huang, Shuheng Wang, Haomiao Wu, Haibin |
author_sort | Zhang, Youzhi |
collection | PubMed |
description | Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates, X, Y, and resistor, R. The output layer has one node representing force, F. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human—computer interactions. |
format | Online Article Text |
id | pubmed-6339246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63392462019-01-23 A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network Zhang, Youzhi Ye, Jinhua Lin, Zhengkang Huang, Shuheng Wang, Haomiao Wu, Haibin Sensors (Basel) Article Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates, X, Y, and resistor, R. The output layer has one node representing force, F. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human—computer interactions. MDPI 2018-12-21 /pmc/articles/PMC6339246/ /pubmed/30577675 http://dx.doi.org/10.3390/s19010027 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Youzhi Ye, Jinhua Lin, Zhengkang Huang, Shuheng Wang, Haomiao Wu, Haibin A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title | A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title_full | A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title_fullStr | A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title_full_unstemmed | A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title_short | A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network |
title_sort | piezoresistive tactile sensor for a large area employing neural network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339246/ https://www.ncbi.nlm.nih.gov/pubmed/30577675 http://dx.doi.org/10.3390/s19010027 |
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