# Understanding Entrainment in Human Groups: Optimising Human-Robot Collaboration from Lessons Learned during Human-Human Collaboration

arXiv: https://arxiv.org/abs/2402.15427 · HTML: https://mlsanity.com/paper/2402.15427/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 50 references that are in the map.
- First posted on arXiv 23 Feb 2024.

## Builds on (most cited first, 2 of 2)

- [The State of Industrial Robotics: Emerging Technologies, Challenges, and Key Research Directions](https://mlsanity.com/paper/2010.14537/) (2020)
- [Movement Coordination in Human-Robot Teams: A Dynamical Systems Approach](https://mlsanity.com/paper/1605.01459/) (2016)

## Abstract (arXiv)

Successful entrainment during collaboration positively affects 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 five 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.