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arXiv · 2409.16009

Modeling and Evaluating Trust Dynamics in Multi-Human Multi-Robot Task Allocation

Ike Obi·Ruiqi Wang·Wonse Jo·Byung-Cheol Min
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Abstract

Trust is essential in human-robot collaboration, particularly in multi-human, multi-robot (MH-MR) teams, where it plays a crucial role in maintaining team cohesion in complex operational environments. Despite its importance, trust is rarely incorporated into task allocation and reallocation algorithms for MH-MR collaboration. While prior research in single-human, single-robot interactions has shown that integrating trust significantly enhances both performance outcomes and user experience, its role in MH-MR task allocation remains underexplored. In this paper, we introduce the Expectation Confirmation Trust (ECT) Model, a novel framework for modeling trust dynamics in MH-MR teams. We evaluate the ECT model against five existing trust models and a no-trust baseline to assess its impact on task allocation outcomes across different team configurations (2H-2R, 5H-5R, and 10H-10R). Our results show that the ECT model improves task success rate, reduces mean completion time, and lowers task error rates. These findings highlight the complexities of trust-based task allocation in MH-MR teams. We discuss the implications of incorporating trust into task allocation algorithms and propose future research directions for adaptive trust mechanisms that balance efficiency and performance in dynamic, multi-agent environments.

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Ike Obi, Ruiqi Wang, Wonse Jo, Byung-Cheol Min. 2024-09-24. Modeling and Evaluating Trust Dynamics in Multi-Human Multi-Robot Task Allocation. https://arxiv.org/abs/2409.16009

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