Mental Workload and Human-Robot Interaction in Collaborative Tasks: A Scoping Review.
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| Title: | Mental Workload and Human-Robot Interaction in Collaborative Tasks: A Scoping Review. |
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| Authors: | Carissoli, Claudia (AUTHOR), Negri, Luca (AUTHOR), Bassi, Marta (AUTHOR), Storm, Fabio Alexander (AUTHOR), Delle Fave, Antonella (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Oct2024, Vol. 40 Issue 20, p6458-6477. 20p. |
| Subjects: | Industrial robots, Human-robot interaction, Work structure, Communication patterns, Organizational communication |
| Abstract: | In human-robot collaboration (HRC), operators work side by side with collaborative robots (cobots), a new type of machines able to function safely on tasks shared with humans. Despite the increasing presence of cobots in factories, the quality of experience associated by workers with HRC is an underexplored topic. This review is focused on the mental workload (MWL) reported by operators interacting with cobots, its major sources, and the potential solutions to optimize it during HRC. Out of 165 papers identified, 23 were selected as specifically devoted to the exploration of workers' MWL in a HRC activity. Cobot motion, predictability, task organization and communication patterns emerged as the major factors contributing to operators' MWL during HRC. Endowing cobots with the capacity to meet both task demands and human needs through modulation of motion rhythm, flexible physical interaction, and more efficient communication patterns may contribute to mitigating workers' MWL. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | In human-robot collaboration (HRC), operators work side by side with collaborative robots (cobots), a new type of machines able to function safely on tasks shared with humans. Despite the increasing presence of cobots in factories, the quality of experience associated by workers with HRC is an underexplored topic. This review is focused on the mental workload (MWL) reported by operators interacting with cobots, its major sources, and the potential solutions to optimize it during HRC. Out of 165 papers identified, 23 were selected as specifically devoted to the exploration of workers' MWL in a HRC activity. Cobot motion, predictability, task organization and communication patterns emerged as the major factors contributing to operators' MWL during HRC. Endowing cobots with the capacity to meet both task demands and human needs through modulation of motion rhythm, flexible physical interaction, and more efficient communication patterns may contribute to mitigating workers' MWL. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10447318 |
| DOI: | 10.1080/10447318.2023.2254639 |
