Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work
Ötting SK, Masjutin L, Steil JJ, Maier GW (2022)
Human Factors 6(4): 1027-1050.
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| Veröffentlicht | Englisch
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Abstract / Bemerkung
Objective: This meta-analysis reviews robot design features of interface, controller, and appearance and statistically summarizes their effect on successful human–robot interaction at work (HRI; i.e., task performance, cooperation, satisfaction, acceptance, trust, mental workload, and situation awareness).
Background: Robots are becoming an integral part of many workplaces. As interactions with employees increase, ensuring success becomes ever more vital. Even though many studies investigated robot design features, an overview on general and specific effects is missing.
Method: Systematic selection of literature and structured coding led to 81 included experimental studies containing 380 effect sizes. Mean effects were calculated using three-level meta-analysis to handle dependencies of multiple effect sizes in one study.
Results: Sufficient feedback through the interface, clear visibility of affordances, and adaptability and autonomy of the controller significantly affect successful HRI, whereas appearance does not. The features of interface and controller affect performance and satisfaction, but do not affect situation awareness and trust. Specific effects of adaptability on cooperation and acceptance, as well as autonomy on workload, could be shown.
Conclusion: Robot design at work needs to cover multiple features of interface and controller to achieve successful HRI that covers not only performance and satisfaction, but also cooperation acceptance and mental workload. More empirical research is needed to investigate mediating mechanisms and underrepresented design features’ effects.
Application: Robot designers should carefully choose design features to balance specific effects and implementation costs with regard to tasks, work design aims, and employee needs in the specific work context.
Stichworte
design features;
interface;
adaptability;
autonomy;
human likeness;
Arbeit4;
metaanalysis;
technology
Erscheinungsjahr
2022
Zeitschriftentitel
Human Factors
Band
6
Ausgabe
4
Seite(n)
1027-1050
ISSN
0018-7208
eISSN
1547-8181
Page URI
https://pub.uni-bielefeld.de/record/2946071
Zitieren
Ötting SK, Masjutin L, Steil JJ, Maier GW. Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors. 2022;6(4):1027-1050.
Ötting, S. K., Masjutin, L., Steil, J. J., & Maier, G. W. (2022). Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors, 6(4), 1027-1050. https://doi.org/10.1177/0018720820966433
Ötting, Sonja Kristine, Masjutin, Lisa, Steil, Jochen J., and Maier, Günter W. 2022. “Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work”. Human Factors 6 (4): 1027-1050.
Ötting, S. K., Masjutin, L., Steil, J. J., and Maier, G. W. (2022). Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors 6, 1027-1050.
Ötting, S.K., et al., 2022. Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors, 6(4), p 1027-1050.
S.K. Ötting, et al., “Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work”, Human Factors, vol. 6, 2022, pp. 1027-1050.
Ötting, S.K., Masjutin, L., Steil, J.J., Maier, G.W.: Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors. 6, 1027-1050 (2022).
Ötting, Sonja Kristine, Masjutin, Lisa, Steil, Jochen J., and Maier, Günter W. “Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work”. Human Factors 6.4 (2022): 1027-1050.
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2020-12-11T12:05:18Z
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Daten bereitgestellt von European Bioinformatics Institute (EBI)
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Daten bereitgestellt von Europe PubMed Central.
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