Partner familiarity enhances performance in a manual precision task

Abstract Understanding human collaborative behavior in tasks with physical interaction is essential for advancing physical human-robot collaboration. Investigating how individuals learn to collaborate over repeated interactions can provide valuable insights for developing robotic agents capable of g...

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Main Authors: Johannes Heidersberger, Jakob Kaiser, Shail Jadav, Lucija Mihić Zidar, Arianna Curioni, Leif Johannsen, Dongheui Lee
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-03341-9
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author Johannes Heidersberger
Jakob Kaiser
Shail Jadav
Lucija Mihić Zidar
Arianna Curioni
Leif Johannsen
Dongheui Lee
author_facet Johannes Heidersberger
Jakob Kaiser
Shail Jadav
Lucija Mihić Zidar
Arianna Curioni
Leif Johannsen
Dongheui Lee
author_sort Johannes Heidersberger
collection DOAJ
description Abstract Understanding human collaborative behavior in tasks with physical interaction is essential for advancing physical human-robot collaboration. Investigating how individuals learn to collaborate over repeated interactions can provide valuable insights for developing robotic agents capable of gradually improving coordination and collaboration performance. Therefore, this study investigated learning behavior in a high-precision task over repeated haptic collaboration. Specifically, we examined if learned collaboration behavior is partner-specific, what collaboration strategies are developed, and if interpersonal differences affect collaboration. Our results indicate that repeated physical collaboration with the same partner allowed for immediate high performance with a familiar partner in subsequent collaborations, whereas adapting to an unfamiliar partner required retraining. Participants used partner-specific collaboration behaviors—in terms of motions and forces—that could be retained in subsequent interactions. Collaborators reduced the variability of their arm motions over repeated collaboration, achieving higher performance, likely due to increased predictability. Collaboration also enabled knowledge transfer between partners, with individual improvement being enhanced when paired with a better-performing partner. These findings suggest that partners in a collaborative precision task optimize their performance by gradually negotiating a joint action strategy, which is reused in subsequent collaborations with familiar partners and carries over to solo task execution.
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institution Kabale University
issn 2045-2322
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publishDate 2025-07-01
publisher Nature Portfolio
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series Scientific Reports
spelling doaj-art-c3de9c6c166d41a8b9f1706b03a249672025-08-20T03:37:20ZengNature PortfolioScientific Reports2045-23222025-07-0115111510.1038/s41598-025-03341-9Partner familiarity enhances performance in a manual precision taskJohannes Heidersberger0Jakob Kaiser1Shail Jadav2Lucija Mihić Zidar3Arianna Curioni4Leif Johannsen5Dongheui Lee6Autonomous Systems Lab, Institute of Computer Technology, TU WienAutonomous Systems Lab, Institute of Computer Technology, TU WienAutonomous Systems Lab, Institute of Computer Technology, TU WienAutonomous Systems Lab, Institute of Computer Technology, TU WienAutonomous Systems Lab, Institute of Computer Technology, TU WienDepartment of Cognition and Experimental Psychology, Institute of Psychology, RWTH Aachen UniversityAutonomous Systems Lab, Institute of Computer Technology, TU WienAbstract Understanding human collaborative behavior in tasks with physical interaction is essential for advancing physical human-robot collaboration. Investigating how individuals learn to collaborate over repeated interactions can provide valuable insights for developing robotic agents capable of gradually improving coordination and collaboration performance. Therefore, this study investigated learning behavior in a high-precision task over repeated haptic collaboration. Specifically, we examined if learned collaboration behavior is partner-specific, what collaboration strategies are developed, and if interpersonal differences affect collaboration. Our results indicate that repeated physical collaboration with the same partner allowed for immediate high performance with a familiar partner in subsequent collaborations, whereas adapting to an unfamiliar partner required retraining. Participants used partner-specific collaboration behaviors—in terms of motions and forces—that could be retained in subsequent interactions. Collaborators reduced the variability of their arm motions over repeated collaboration, achieving higher performance, likely due to increased predictability. Collaboration also enabled knowledge transfer between partners, with individual improvement being enhanced when paired with a better-performing partner. These findings suggest that partners in a collaborative precision task optimize their performance by gradually negotiating a joint action strategy, which is reused in subsequent collaborations with familiar partners and carries over to solo task execution.https://doi.org/10.1038/s41598-025-03341-9Partner familiarityCollaborative learningJoint actionHuman-human interaction
spellingShingle Johannes Heidersberger
Jakob Kaiser
Shail Jadav
Lucija Mihić Zidar
Arianna Curioni
Leif Johannsen
Dongheui Lee
Partner familiarity enhances performance in a manual precision task
Scientific Reports
Partner familiarity
Collaborative learning
Joint action
Human-human interaction
title Partner familiarity enhances performance in a manual precision task
title_full Partner familiarity enhances performance in a manual precision task
title_fullStr Partner familiarity enhances performance in a manual precision task
title_full_unstemmed Partner familiarity enhances performance in a manual precision task
title_short Partner familiarity enhances performance in a manual precision task
title_sort partner familiarity enhances performance in a manual precision task
topic Partner familiarity
Collaborative learning
Joint action
Human-human interaction
url https://doi.org/10.1038/s41598-025-03341-9
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AT jakobkaiser partnerfamiliarityenhancesperformanceinamanualprecisiontask
AT shailjadav partnerfamiliarityenhancesperformanceinamanualprecisiontask
AT lucijamihiczidar partnerfamiliarityenhancesperformanceinamanualprecisiontask
AT ariannacurioni partnerfamiliarityenhancesperformanceinamanualprecisiontask
AT leifjohannsen partnerfamiliarityenhancesperformanceinamanualprecisiontask
AT dongheuilee partnerfamiliarityenhancesperformanceinamanualprecisiontask