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The Effect of Anthropomorphism on Trust in an Industrial Human-Robot Interaction
Mobile Robotics and Olfaction Lab, Örebro University, Sweden.
Machine Perception and Interaction Lab, Örebro University, Sweden.
Mobile Robotics and Olfaction Lab, Örebro University, Sweden.
Robert Bosch GmbH, Corporate Research, Stuttgart, Germany.
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2022 (English)In: Trust, Acceptance and Social Cues in Human-Robot Interaction - SCRITA Workshop: IEEE International Conference on Robot & Human Interactive Communication 29 August 2022, Naples (Italy) / [ed] Alessandra Rossi; Patrick Holthaus; Silvia Moros; Gabriella Lakatos, IEEE, 2022, article id arXiv:2208.11090Conference paper, Published paper (Refereed)
Abstract [en]

Robots are increasingly deployed in spaces shared with humans, including home settings and industrial environments. In these environments, the interaction between humans and robots (HRI) is crucial for safety, legibility, andefficiency. A key factor in HRI is trust, which modulates the acceptance of the system. Anthropomorphism has been shown to modulate trust development in a robot, but robotsin industrial environments are usually not anthropomorphic. We designed a simple interaction in an industrial environment in which an anthropomorphic mock driver (ARMoD) robot simulates driving an autonomous guided vehicle (AGV). The task consisted of a human crossing paths with the AGV, with or without the ARMoD mounted on the top, in a narrow corridor. The human and the system needed to negotiate trajectories when crossing paths, meaning that the human had to attend to the trajectory of the robot to avoid a collision with it. There was a significant increment in the reported trust scores in the condition where the ARMoD was present, showing that the presence of an anthropomorphic robot is enough to modulate the trust, even in limited interactions as the one we present here.

Place, publisher, year, edition, pages
IEEE, 2022. article id arXiv:2208.11090
Series
SCRITA Workshop Proceedings
National Category
Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-21942DOI: 10.48550/arXiv.2208.14637OAI: oai:DiVA.org:his-21942DiVA, id: diva2:1703218
Conference
SCRITA Workshop held in conjunction with 31st IEEE International Conference on Robot & Human Interactive Communication, 29 August - 3 September 2022, Naples (Italy)
Funder
EU, Horizon 2020, 101017274 (DARKO)EU, Horizon 2020, 754285
Note

CC BY-SA 4.0

This work was supported by the European Union’s Horizon 2020 researchand innovation program under grant agreement No. 101017274 (DARKO) and grant agreement No. 754285

Available from: 2022-10-12 Created: 2022-10-12 Last updated: 2023-01-02Bibliographically approved

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Billing, Erik Alexander

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