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HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load
In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are ex...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029803/ https://www.ncbi.nlm.nih.gov/pubmed/37361336 http://dx.doi.org/10.1007/s10845-023-02096-2 |
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author | Yang, Wenhao Xiao, Qinqin Zhang, Yunbo |
author_facet | Yang, Wenhao Xiao, Qinqin Zhang, Yunbo |
author_sort | Yang, Wenhao |
collection | PubMed |
description | In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are experiencing a labor shortage. An essential question, therefore, is: how would a new robot programming method help novice users complete complex tasks effectively, efficiently, and intuitively? To answer this question, we proposed HA[Formula: see text] bot, a novel human-centered augmented reality programming interface with awareness of cognitive load. Using NASA’s system design theory and the cognitive load theory, a set of guidelines for designing an AR-based human-robot interaction system is obtained through a human-centered design process. Based on these guidelines, we designed and implemented a human-in-the-loop workflow with features for cognitive load management. The effectiveness and efficiency of HA[Formula: see text] bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HA[Formula: see text] bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HA[Formula: see text] bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety. |
format | Online Article Text |
id | pubmed-10029803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-100298032023-03-21 HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load Yang, Wenhao Xiao, Qinqin Zhang, Yunbo J Intell Manuf Article In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are experiencing a labor shortage. An essential question, therefore, is: how would a new robot programming method help novice users complete complex tasks effectively, efficiently, and intuitively? To answer this question, we proposed HA[Formula: see text] bot, a novel human-centered augmented reality programming interface with awareness of cognitive load. Using NASA’s system design theory and the cognitive load theory, a set of guidelines for designing an AR-based human-robot interaction system is obtained through a human-centered design process. Based on these guidelines, we designed and implemented a human-in-the-loop workflow with features for cognitive load management. The effectiveness and efficiency of HA[Formula: see text] bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HA[Formula: see text] bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HA[Formula: see text] bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety. Springer US 2023-03-21 /pmc/articles/PMC10029803/ /pubmed/37361336 http://dx.doi.org/10.1007/s10845-023-02096-2 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Yang, Wenhao Xiao, Qinqin Zhang, Yunbo HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title | HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title_full | HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title_fullStr | HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title_full_unstemmed | HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title_short | HA[Formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
title_sort | ha[formula: see text] bot: a human-centered augmented reality robot programming method with the awareness of cognitive load |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029803/ https://www.ncbi.nlm.nih.gov/pubmed/37361336 http://dx.doi.org/10.1007/s10845-023-02096-2 |
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