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Facially expressive humanoid robotic face

Realistic humanoid robots have emerged in the last two decades but the emotional intelligence of these machines has been limited. To teach humanoids how to emotionally communicate with humans, researchers have been increasingly relying on machine learning algorithms. While the software used to imple...

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Detalles Bibliográficos
Autores principales: Faraj, Zanwar, Selamet, Mert, Morales, Carlos, Torres, Patricio, Hossain, Maimuna, Chen, Boyuan, Lipson, Hod
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041256/
https://www.ncbi.nlm.nih.gov/pubmed/35492039
http://dx.doi.org/10.1016/j.ohx.2020.e00117
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author Faraj, Zanwar
Selamet, Mert
Morales, Carlos
Torres, Patricio
Hossain, Maimuna
Chen, Boyuan
Lipson, Hod
author_facet Faraj, Zanwar
Selamet, Mert
Morales, Carlos
Torres, Patricio
Hossain, Maimuna
Chen, Boyuan
Lipson, Hod
author_sort Faraj, Zanwar
collection PubMed
description Realistic humanoid robots have emerged in the last two decades but the emotional intelligence of these machines has been limited. To teach humanoids how to emotionally communicate with humans, researchers have been increasingly relying on machine learning algorithms. While the software used to implement machine learning algorithms is largely open source, facially expressive humanoid robots are expensive and inaccessible to most people, thus limiting the number of researchers in this field. This paper aims to aid potential artificial intelligence researchers by providing a relatively inexpensive, open-source robot that can serve as a platform for research into emotional communication between humans and machines. Eva, the robot described in this paper, is an adult-sized humanoid head that can emulate human facial expressions, head movements, and speech through the use of 25 muscles, including 12 facial muscles that can produce a maximum skin displacement of 15 mm.
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spelling pubmed-90412562022-04-27 Facially expressive humanoid robotic face Faraj, Zanwar Selamet, Mert Morales, Carlos Torres, Patricio Hossain, Maimuna Chen, Boyuan Lipson, Hod HardwareX Article Realistic humanoid robots have emerged in the last two decades but the emotional intelligence of these machines has been limited. To teach humanoids how to emotionally communicate with humans, researchers have been increasingly relying on machine learning algorithms. While the software used to implement machine learning algorithms is largely open source, facially expressive humanoid robots are expensive and inaccessible to most people, thus limiting the number of researchers in this field. This paper aims to aid potential artificial intelligence researchers by providing a relatively inexpensive, open-source robot that can serve as a platform for research into emotional communication between humans and machines. Eva, the robot described in this paper, is an adult-sized humanoid head that can emulate human facial expressions, head movements, and speech through the use of 25 muscles, including 12 facial muscles that can produce a maximum skin displacement of 15 mm. Elsevier 2020-06-12 /pmc/articles/PMC9041256/ /pubmed/35492039 http://dx.doi.org/10.1016/j.ohx.2020.e00117 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Faraj, Zanwar
Selamet, Mert
Morales, Carlos
Torres, Patricio
Hossain, Maimuna
Chen, Boyuan
Lipson, Hod
Facially expressive humanoid robotic face
title Facially expressive humanoid robotic face
title_full Facially expressive humanoid robotic face
title_fullStr Facially expressive humanoid robotic face
title_full_unstemmed Facially expressive humanoid robotic face
title_short Facially expressive humanoid robotic face
title_sort facially expressive humanoid robotic face
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041256/
https://www.ncbi.nlm.nih.gov/pubmed/35492039
http://dx.doi.org/10.1016/j.ohx.2020.e00117
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