Miyauchi, G. orcid.org/0000-0002-3349-6765, Lopes, Y.K. and Gross, R. orcid.org/0000-0003-1826-1375 (2023) Sharing the control of robot swarms among multiple human operators: a user study. In: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Proceedings. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 01-05 Oct 2023, Detroit, Michigan, USA. Institute of Electrical and Electronics Engineers (IEEE) , pp. 8847-8853. ISBN 9781665491914
Abstract
Simultaneously controlling multiple robot swarms is challenging for a single human operator. When involving multiple operators, however, they can each focus on controlling a specific robot swarm, which helps distribute the cognitive workload. They could also exchange some robots with each other in response to the requirements of the tasks they discover. This paper investigates the ability of multiple operators to dynamically share the control of robot swarms and the effects of different communication types on performance and human factors. A total of 52 participants completed an experiment in which they were randomly paired to form a team. In a 2×2 mixed factorial study, participants were split into two groups by communication type (direct vs. indirect). Both groups experienced different robot-sharing conditions (robot-sharing vs. no-robot-sharing). Results show that although the ability to share robots did not necessarily increase task scores, it allowed the operators to switch between working independently and collaboratively, reduced the total energy consumed by the swarm, and was considered useful by the participants.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. Except as otherwise noted, this author-accepted version of a paper published in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)] is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Training; Atmospheric measurements; Human factors; Switches; Particle measurements; Task analysis; Robots |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number UK RESEARCH AND INNOVATION 10048272 101093046 UK Research and Innovation 10048272 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Aug 2023 15:28 |
Last Modified: | 04 Jan 2024 16:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/IROS55552.2023.10342457 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202313 |