Abstract
Information technology is advancing rapidly, and with it, robots. Nowadays, the interaction between robots and humans changes e.g., from the execution of simple movements towards a new level where they can perform different work-related aspects almost completely independently. Therefore, especially in production, the prevention of negative emotions is important. Consequently, attention should not only be focused on the physical safety of workers but also on their acceptance, fears and biases. An experimental study focuses on the impact of two different interaction instruction variants, with and without direct human-robot interaction, on acceptance, trust, performance and participants’ psychophysiological (ECG and EDA) reactions during human-robot interaction with an industrial robot (Horst600, fruitcore robotics GmbH). Furthermore, the movement speed of the robot was variated (five levels) within a simple handover task. Overall, 14 men and 5 women participated in the study. They were randomly assigned to the two different instruction variants. On the one hand, the results indicate significant differences regarding the movement speed levels and interestingly, on the other hand, the results did not show significant effects regarding the investigated instructions. To sum it up, the results of the study should help to understand how people perceive a physical interaction with an industrial robot.
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Author’s Statement
The authors state no conflict of interest. Informed consent has been obtained from all individuals included in this study. The research has been approved by the ethics’ committee of Furtwangen University. The authors would like to thank all participants that participated in the study as well as Peter Anders and Katharina Gleichauf for their support.
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Wagner-Hartl, V., Nakladal, S., Koch, T., Babajic, D., Mazur, S., Birkle, J. (2023). Influence of Movement Speed and Interaction Instructions on Subjective Assessments, Performance and Psychophysiological Reactions During Human-Robot Interaction. In: Kurosu, M., et al. HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14054. Springer, Cham. https://doi.org/10.1007/978-3-031-48038-6_29
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