Abstract
Existing research on human perception of robot appearance has focused heavily on anthropomorphism and humanoid robots, with less attention paid to visual form attributes and non-humanoid systems. In this paper, we propose robot visual form attribute traits and a beginning sampling of robot arms with which to expand the understanding of robot visual form effects. We conduct an online survey-based within-subjects study to gather ratings of these visual form attributes, as well as standard social attributes, for each arm. Our data collection methods include two-alternative forced choice questions and sets of Likert-type self-reports related to individual visual stimuli. The results from this exploratory study show that even within non-humanoid robots of similar structure, the visual elements have a significant effect on perceptions of robot social characteristics such as warmth, competency, and safety.
R. C. Preston and N. Raghunath—Contributed equally to this work.
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Acknowledgments
We thank Dr. Cindy Grimm, Alejandro Velasquez, and Joshua Campbell for providing the Kinova and UR5e robot arms and posing them for photographing.
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Preston, R.C., Raghunath, N., Sanchez, C.A., Fitter, N.T. (2022). “Armed” and Dangerous: How Visual Form Influences Perceptions of Robot Arms. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_47
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