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Tracking human interactions with a commercially-available robot over multiple days
Background: As research examining human-robot interaction moves from the laboratory to the real world, studies seeking to examine how people interact with robots face the question of which robotic platform to employ to collect data in situ. To facilitate the study of a broad range of individuals, fr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445930/ https://www.ncbi.nlm.nih.gov/pubmed/37645308 http://dx.doi.org/10.12688/openreseurope.14824.1 |
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author | Hortensius, Ruud Chaudhury, Bishakha Hoffmann, Martin Cross, Emily |
author_facet | Hortensius, Ruud Chaudhury, Bishakha Hoffmann, Martin Cross, Emily |
author_sort | Hortensius, Ruud |
collection | PubMed |
description | Background: As research examining human-robot interaction moves from the laboratory to the real world, studies seeking to examine how people interact with robots face the question of which robotic platform to employ to collect data in situ. To facilitate the study of a broad range of individuals, from children to clinical populations, across diverse environments, from homes to schools, a robust, reproducible, low-cost and easy-to-use robotic platform is needed. Methods: We describe how a commercially available off-the-shelf robot, Cozmo, can be used to study embodied human-robot interactions in a wide variety of settings, including the user’s home. We describe the steps required to use this affordable and flexible platform for longitudinal human-robot interaction studies. First, we outline the technical specifications and requirements of this platform and accessories. We then show how log files containing detailed data on the human-robot interaction can be collected and extracted. Finally, we detail the types of information that can be retrieved from these data. Results: We present findings from a validation that mapped the behavioural repertoire of the Cozmo robot and introduce an accompanying interactive emotion classification tool to use with this robot. This tool combined with the data extracted from the log files can provide the necessary details to understand the psychological consequences of long-term interactions. Conclusions: This low-cost robotic platform has the potential to provide the field with a variety of valuable new possibilities to study the social cognitive processes underlying human-robot interactions within and beyond the research laboratory, which are user-driven and unconstrained in both time and place. |
format | Online Article Text |
id | pubmed-10445930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-104459302023-08-29 Tracking human interactions with a commercially-available robot over multiple days Hortensius, Ruud Chaudhury, Bishakha Hoffmann, Martin Cross, Emily Open Res Eur Method Article Background: As research examining human-robot interaction moves from the laboratory to the real world, studies seeking to examine how people interact with robots face the question of which robotic platform to employ to collect data in situ. To facilitate the study of a broad range of individuals, from children to clinical populations, across diverse environments, from homes to schools, a robust, reproducible, low-cost and easy-to-use robotic platform is needed. Methods: We describe how a commercially available off-the-shelf robot, Cozmo, can be used to study embodied human-robot interactions in a wide variety of settings, including the user’s home. We describe the steps required to use this affordable and flexible platform for longitudinal human-robot interaction studies. First, we outline the technical specifications and requirements of this platform and accessories. We then show how log files containing detailed data on the human-robot interaction can be collected and extracted. Finally, we detail the types of information that can be retrieved from these data. Results: We present findings from a validation that mapped the behavioural repertoire of the Cozmo robot and introduce an accompanying interactive emotion classification tool to use with this robot. This tool combined with the data extracted from the log files can provide the necessary details to understand the psychological consequences of long-term interactions. Conclusions: This low-cost robotic platform has the potential to provide the field with a variety of valuable new possibilities to study the social cognitive processes underlying human-robot interactions within and beyond the research laboratory, which are user-driven and unconstrained in both time and place. F1000 Research Limited 2022-08-16 /pmc/articles/PMC10445930/ /pubmed/37645308 http://dx.doi.org/10.12688/openreseurope.14824.1 Text en Copyright: © 2022 Hortensius R et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Method Article Hortensius, Ruud Chaudhury, Bishakha Hoffmann, Martin Cross, Emily Tracking human interactions with a commercially-available robot over multiple days |
title | Tracking human interactions with a commercially-available robot over multiple days |
title_full | Tracking human interactions with a commercially-available robot over multiple days |
title_fullStr | Tracking human interactions with a commercially-available robot over multiple days |
title_full_unstemmed | Tracking human interactions with a commercially-available robot over multiple days |
title_short | Tracking human interactions with a commercially-available robot over multiple days |
title_sort | tracking human interactions with a commercially-available robot over multiple days |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445930/ https://www.ncbi.nlm.nih.gov/pubmed/37645308 http://dx.doi.org/10.12688/openreseurope.14824.1 |
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