Pilot Study on the Relationship Between Acceptance of Collaborative Robots and Stress

Erika Lutin, Shirley Elprama, Cornelis Jan, Patricia Leconte, Bart Van Doninck, Maarten Witters, Walter De Raedt, An Jacobs

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
55 Downloads (Pure)

Abstract

Currently, collaborative robots (cobots) are mostly programmed to do one task repetitively. They can be programmed at different speeds and work near human operators. The goal of our research was to investigate the effect of robot speed on acceptance, subjective and objective stress, and cognitive workload of individuals. Therefore, we organized a repeated measures experiment in which participants (N = 25) conducted an assembly task with the YuMi cobot from ABB at a low and at a high speed. Subjective and physiological responses were collected, and participants were subjected to a standardized stress test. Our results indicate that when working with a cobot at a high speed, people believe they can work faster and be more productive but also experience a higher workload and higher perceived stress. We also found that tonic EDA is a significant physiological predictor for monitoring perceived stress in humans. We observed a greater relative increase in tonic EDA from baseline to task execution during high-speed mode compared to low-speed mode. Additionally, this increase in tonic EDA significantly correlated with participants’ perceived stress levels. However, workload could not be predicted by any of the physiological measures. Future research should explore the effect of higher cobot working speeds and the use of physiological measures (such as stress) as input to guide the collaboration between individuals and cobots.
Original languageEnglish
Pages (from-to)1475-1488
Number of pages14
JournalInternational Journal of Social Robotics
Volume16
Issue number6
DOIs
Publication statusPublished - 27 Jun 2024

Bibliographical note

Funding Information:
We thank VLAIO for supporting this research under the \u201CLiving Labs Smart Factories\u201D (HBC.2017.0801) and we thank the European Union\u2019s Horizon 2020 Research and Innovation Programme (H2020-ICT-2019-2/ 2019\u20132023) for supporting this work with funding for EU Sophia under grant agreement No. 871237. This work was supported by a PhD fellowship from the Research Foundation - Flanders (FWO) awarded to EL (1SB4719N).

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature B.V. 2024.

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