Trust and Acceptance of Multi-Robot Systems "in the Wild". A Roadmap exemplified within the EU-Project BugWright2
Schroepfer, Pete, Schauffel, Nathalie, Gründling, Jan, Ellwart, Thomas, Weyers, Benjamin, Pradalier, Cédric
–arXiv.org Artificial Intelligence
This paper outlines a roadmap to effectively leverage shared mental models in multi-robot, multi-stakeholder scenarios, drawing on experiences from the BugWright2 project. The discussion centers on an autonomous multi-robot systems designed for ship inspection and maintenance. A significant challenge in the development and implementation of this system is the calibration of trust. To address this, the paper proposes that trust calibration can be managed and optimized through the creation and continual updating of shared and accurate mental models of the robots. Strategies to promote these mental models, including cross-training, briefings, debriefings, and task-specific elaboration and visualization, are examined. Additionally, the crucial role of an adaptable, distributed, and well-structured user interface (UI) is discussed.
arXiv.org Artificial Intelligence
Dec-13-2023
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- Europe
- North America > United States (0.04)
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- Research Report (0.50)
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- Health & Medicine > Consumer Health (0.36)
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