Understanding entrainment in human groups: optimising human-robot collaboration from lessons learned during human-human collaboration

Schneiders, Eike, Fourie, Christopher, Celestin, Stanley, Shah, Julie and Jung, Malte (2024) Understanding entrainment in human groups: optimising human-robot collaboration from lessons learned during human-human collaboration. In CHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Sytems. Association for Computing Machinery. pp. 1-13 . (doi:10.1145/3613904.3642427).

Abstract

Successful entrainment during collaboration positively afects trust, willingness to collaborate, and likeability towards collaborators. In this paper, we present a mixed-method study to investigate characteristics of successful entrainment leading to pair and group-based synchronisation. Drawing inspiration from industrial settings, we designed a fast-paced, short-cycle repetitive task. Using motion tracking, we investigated entrainment in both dyadic and triadic task completion. Furthermore, we utilise audio-video recordings and semi-structured interviews to contextualise participants' experiences. This paper contributes to the Human-Computer/Robot Interaction (HCI/HRI) literature using a human-centred approach to identify characteristics of entrainment during pair- and group-based collaboration. We present fve characteristics related to successful entrainment. These are related to the occurrence of entrainment, leader-follower patterns, interpersonal communication, the importance of the point-of-assembly, and the value of acoustic feedback. Finally, we present three design considerations for future research and design on collaboration with robots.

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Contributors

Author: Eike Schneiders

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