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Take one for the team: The effects of error severity in collaborative tasks with social robots
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-3729-157x
KTH.
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, Perception and Learning, RPL.
2019 (English)In: IVA 2019 - Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents, Association for Computing Machinery (ACM), 2019, p. 151-158Conference paper, Published paper (Refereed)
Abstract [en]

We explore the effects of robot failure severity (no failure vs. lowimpact vs. high-impact) on people's subjective ratings of the robot. We designed an escape room scenario in which one participant teams up with a remotely-controlled Pepper robot.We manipulated the robot's performance at the end of the game: The robot would either correctly follow the participant's instructions (control condition), the robot would fail but people could still complete the task of escaping the room (low-impact condition), or the robot's failure would cause the game to be lost (high-impact condition). Results showed no difference across conditions for people's ratings of the robot in terms of warmth, competence, and discomfort. However, people in the low-impact condition had significantly less faith in the robot's robustness in future escape room scenarios. Open-ended questions revealed interesting trends that are worth pursuing in the future: people may view task performance as a team effort and may blame their team or themselves more for the robot failure in case of a high-impact failure as compared to the low-impact failure.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2019. p. 151-158
Keywords [en]
Failure, Human-robot interaction, Socially collaborative robots
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-262609DOI: 10.1145/3308532.3329475Scopus ID: 2-s2.0-85069747331ISBN: 9781450366724 (print)OAI: oai:DiVA.org:kth-262609DiVA, id: diva2:1362906
Conference
19th ACM International Conference on Intelligent Virtual Agents, IVA 2019; Paris; France; 2 July 2019 through 5 July 2019
Note

QC 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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More styles
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Output format
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