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SVAS(3): Strain Vector Aided Sensorization of Soft Structures
Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168483/ https://www.ncbi.nlm.nih.gov/pubmed/25036332 http://dx.doi.org/10.3390/s140712748 |
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author | Culha, Utku Nurzaman, Surya G. Clemens, Frank Iida, Fumiya |
author_facet | Culha, Utku Nurzaman, Surya G. Clemens, Frank Iida, Fumiya |
author_sort | Culha, Utku |
collection | PubMed |
description | Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS(3)), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations. |
format | Online Article Text |
id | pubmed-4168483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41684832014-09-19 SVAS(3): Strain Vector Aided Sensorization of Soft Structures Culha, Utku Nurzaman, Surya G. Clemens, Frank Iida, Fumiya Sensors (Basel) Article Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS(3)), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations. MDPI 2014-07-17 /pmc/articles/PMC4168483/ /pubmed/25036332 http://dx.doi.org/10.3390/s140712748 Text en © 2014 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 license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Culha, Utku Nurzaman, Surya G. Clemens, Frank Iida, Fumiya SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title | SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title_full | SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title_fullStr | SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title_full_unstemmed | SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title_short | SVAS(3): Strain Vector Aided Sensorization of Soft Structures |
title_sort | svas(3): strain vector aided sensorization of soft structures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168483/ https://www.ncbi.nlm.nih.gov/pubmed/25036332 http://dx.doi.org/10.3390/s140712748 |
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