I Like the Way You Move: A Mixed-Methods Approach for Studying the Effects of Robot Motion on Collaborative Human Robot Interaction

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Abstract

Human robot collaboration is an increasingly relevant area within Human Robot Interaction. As robots move into dynamic environments and engage in collaborative tasks with people, there is a need to further understand how perceptual and communication cues facilitate and support Human Robot Collaboration. Building on prior Human Robot Interaction studies, we developed a mixed-methods approach for studying the effects of expressive movements of an industrial robot arm engaged in a collaborative drawing task. The purpose was to evaluate the effects of different movement qualities on participant experience while collaborating with a robot. We present our approach and the results of the experiments. Although we did not identify any significant difference in interactions where the robot moved expressively, our study highlights the importance of in-the-wild experiments and strategies for combining qualitative and quantitative methodologies.

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Pedersen, J. E., Christensen, K. W., Herath, D., & Jochum, E. (2020). I Like the Way You Move: A Mixed-Methods Approach for Studying the Effects of Robot Motion on Collaborative Human Robot Interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12483 LNAI, pp. 73–84). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62056-1_7

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