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Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design
Faces of android robots are one of the most important interfaces to communicate with humans quickly and effectively, as they need to match the expressive capabilities of the human face, it is no wonder that they are complex mechanical systems containing inevitable non-linear and hysteresis elements...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805635/ https://www.ncbi.nlm.nih.gov/pubmed/33500998 http://dx.doi.org/10.3389/frobt.2018.00119 |
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author | Ishihara, Hisashi Wu, Binyi Asada, Minoru |
author_facet | Ishihara, Hisashi Wu, Binyi Asada, Minoru |
author_sort | Ishihara, Hisashi |
collection | PubMed |
description | Faces of android robots are one of the most important interfaces to communicate with humans quickly and effectively, as they need to match the expressive capabilities of the human face, it is no wonder that they are complex mechanical systems containing inevitable non-linear and hysteresis elements derived from their non-rigid components. Identifying the input-output response properties of this complex system is necessary to design surface deformations accurately and precisely. However, to date, android faces have been used without careful system identification and thus remain black boxes. In this study, the static responses of three-dimensional displacements were investigated for 116 facial surface points against a discrete trapezoidal input provided to each actuator in the face of a child-type android robot Affetto. The results show that the response curves can be modeled with hysteretical sigmoid functions, and that the response properties of the face actuators, including sensitivity, hysteresis, and dyssynchrony, were quite different. The paper further proposes a design methodology for surface motion patterns based on the obtained response models. Design results thus obtained indicate that the proposed response properties enable us to predict the design results, and that the proposed design methodology can cancel the differences among the response curves of the actuators. The proposed identification and quantitative evaluation method can be applied to advanced android face studies instead of conventional qualitative evaluation methodologies. |
format | Online Article Text |
id | pubmed-7805635 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78056352021-01-25 Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design Ishihara, Hisashi Wu, Binyi Asada, Minoru Front Robot AI Robotics and AI Faces of android robots are one of the most important interfaces to communicate with humans quickly and effectively, as they need to match the expressive capabilities of the human face, it is no wonder that they are complex mechanical systems containing inevitable non-linear and hysteresis elements derived from their non-rigid components. Identifying the input-output response properties of this complex system is necessary to design surface deformations accurately and precisely. However, to date, android faces have been used without careful system identification and thus remain black boxes. In this study, the static responses of three-dimensional displacements were investigated for 116 facial surface points against a discrete trapezoidal input provided to each actuator in the face of a child-type android robot Affetto. The results show that the response curves can be modeled with hysteretical sigmoid functions, and that the response properties of the face actuators, including sensitivity, hysteresis, and dyssynchrony, were quite different. The paper further proposes a design methodology for surface motion patterns based on the obtained response models. Design results thus obtained indicate that the proposed response properties enable us to predict the design results, and that the proposed design methodology can cancel the differences among the response curves of the actuators. The proposed identification and quantitative evaluation method can be applied to advanced android face studies instead of conventional qualitative evaluation methodologies. Frontiers Media S.A. 2018-10-23 /pmc/articles/PMC7805635/ /pubmed/33500998 http://dx.doi.org/10.3389/frobt.2018.00119 Text en Copyright © 2018 Ishihara, Wu and Asada. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Ishihara, Hisashi Wu, Binyi Asada, Minoru Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title | Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title_full | Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title_fullStr | Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title_full_unstemmed | Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title_short | Identification and Evaluation of the Face System of a Child Android Robot Affetto for Surface Motion Design |
title_sort | identification and evaluation of the face system of a child android robot affetto for surface motion design |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805635/ https://www.ncbi.nlm.nih.gov/pubmed/33500998 http://dx.doi.org/10.3389/frobt.2018.00119 |
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