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Take a Chance on Me: How Robot Performance and Risk Behaviour Affects Trust and Risk-Taking
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-6158-4818
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-7252-8133
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-3432-6151
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-1170-7162
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2025 (English)In: HRI 2025 - Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction, Institute of Electrical and Electronics Engineers (IEEE) , 2025, p. 391-399Conference paper, Published paper (Refereed)
Abstract [en]

Real-world human-robot interactions often encompass uncertainty. This uncertainty can be handled in different ways, for example by designing robot planners to be more or less risk-tolerant. However, how users actually perceive different risk-taking behaviours in robots has yet to be described. Additionally, in the absence of guarantees on optimal robot performance, the interaction between risk and performance on user perceptions is also unclear. To address this gap, we conducted a user study with 84 participants investigating how robot performance and risk behaviour affects users' trust and risk-taking decisions. Participants collaborated with a Franka robot arm to perform a block-stacking task. We compared a robot which displays consistent but sub-optimal behaviours to a robot displaying risky but occasionally optimal behaviour. Risky robot behaviour led to higher trust than consistent behaviour when the robot was on average good at stacking blocks (high expectation), but lower trust when the robot was on average bad at stacking blocks (low expectation). Individual risk-willingness also predicted likelihood of selecting the risky robot over the consistent robot for future interactions, but only when the average expectation was low. These findings have implications for risk-aware planning and decision-making in mixed human-robot systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025. p. 391-399
Keywords [en]
collaborative robot, failure, risk-taking, trust, user study
National Category
Robotics and automation Human Computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-363768DOI: 10.1109/HRI61500.2025.10973966Scopus ID: 2-s2.0-105004879443OAI: oai:DiVA.org:kth-363768DiVA, id: diva2:1959863
Conference
20th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2025, Melbourne, Australia, Mar 4 2025 - Mar 6 2025
Note

Part of ISBN 9798350378931

QC 20250527

Available from: 2025-05-21 Created: 2025-05-21 Last updated: 2025-05-27Bibliographically approved

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Stower, RebeccaGautier, AnnaWozniak, Maciej K.Jensfelt, PatricTumova, JanaLeite, Iolanda

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