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Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor

Human skin is capable of sensing various types of forces with high resolution and accuracy. The development of an artificial sense of touch needs to address these properties, while retaining scalability to large surfaces with arbitrary shapes. The vision-based tactile sensor proposed in this article...

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Detalles Bibliográficos
Autores principales: Sferrazza, Carmelo, D’Andrea, Raffaello
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412824/
https://www.ncbi.nlm.nih.gov/pubmed/30813292
http://dx.doi.org/10.3390/s19040928
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author Sferrazza, Carmelo
D’Andrea, Raffaello
author_facet Sferrazza, Carmelo
D’Andrea, Raffaello
author_sort Sferrazza, Carmelo
collection PubMed
description Human skin is capable of sensing various types of forces with high resolution and accuracy. The development of an artificial sense of touch needs to address these properties, while retaining scalability to large surfaces with arbitrary shapes. The vision-based tactile sensor proposed in this article exploits the extremely high resolution of modern image sensors to reconstruct the normal force distribution applied to a soft material, whose deformation is observed on the camera images. By embedding a random pattern within the material, the full resolution of the camera can be exploited. The design and the motivation of the proposed approach are discussed with respect to a simplified elasticity model. An artificial deep neural network is trained on experimental data to perform the tactile sensing task with high accuracy for a specific indenter, and with a spatial resolution and a sensing range comparable to the human fingertip.
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spelling pubmed-64128242019-04-03 Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor Sferrazza, Carmelo D’Andrea, Raffaello Sensors (Basel) Article Human skin is capable of sensing various types of forces with high resolution and accuracy. The development of an artificial sense of touch needs to address these properties, while retaining scalability to large surfaces with arbitrary shapes. The vision-based tactile sensor proposed in this article exploits the extremely high resolution of modern image sensors to reconstruct the normal force distribution applied to a soft material, whose deformation is observed on the camera images. By embedding a random pattern within the material, the full resolution of the camera can be exploited. The design and the motivation of the proposed approach are discussed with respect to a simplified elasticity model. An artificial deep neural network is trained on experimental data to perform the tactile sensing task with high accuracy for a specific indenter, and with a spatial resolution and a sensing range comparable to the human fingertip. MDPI 2019-02-22 /pmc/articles/PMC6412824/ /pubmed/30813292 http://dx.doi.org/10.3390/s19040928 Text en © 2019 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
Sferrazza, Carmelo
D’Andrea, Raffaello
Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title_full Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title_fullStr Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title_full_unstemmed Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title_short Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor
title_sort design, motivation and evaluation of a full-resolution optical tactile sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412824/
https://www.ncbi.nlm.nih.gov/pubmed/30813292
http://dx.doi.org/10.3390/s19040928
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