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Role specialization enables superior task performance by human dyads than individuals

Asuka Takai,Qiushi Fu,Yuzuru Doibata,G. Lisi,Toshiki Tsuchiya,Keivan Mojtahedi,T. Yoshioka,Mitsuo Kawato,J. Morimoto,Marco Santello

Published 2025 in The international journal of robotics research

ABSTRACT

It is generally accepted that collaboration yields better performance than when the same task is performed by individuals operating alone. Is collaboration always superior to individual performances, or do its benefits depend on whether collaborating individuals have the same or different roles? Here, participants performed tasks to transport a virtual beam while keeping it horizontal. Twin robotic manipulanda were coupled to the simulated beam with either symmetric or asymmetric dynamics. In paired modes, two participants grasped the robot handles, whereas in solo modes, individual participants grasped both handles with their two hands. Computational simulations revealed that this task could be successfully performed regardless of whether roles were the same or different for each beam dynamics. However, pairs performed better than individuals after two participants spontaneously assumed different roles, co-adapting by learning in asymmetric dynamics, with one participant leading the movement and exerting more force than the other. In contrast, individuals performed better than pairs if pairs did not assume different roles. Our findings suggest that better performance by pairs than individuals is not a general phenomenon, but that collaboration only yields better performance if role specialization spontaneously emerges in such interactions.

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