Shared Mental Models to Support Distributed Human-Robot Teaming in Space

Felix Gervits, T. Fong, Matthias Scheutz
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引用次数: 9

Abstract

Effective human-robot interaction (HRI) is a critical requirement for current and future space operations. However, given the limitations of autonomous technologies, robots are not yet capable of coordinating with human crew as peers under real-world mission constraints. Due to the complexity inherent in space robotics operations, it is crucial that robots are able to coordinate the various aspects of human-robot teaming and the task at hand. In this paper, we extend our Shared Mental Model (SMM) interaction framework to show how it can be used to overcome some of the challenges inherent in distributed HRI and facilitate coordination in space robotics teams. Since this framework has not yet been implemented in real systems, we conducted an exploratory study to identify potential benefits that the SMM mechanisms can afford in a task domain involving simulated free-flying robot assistants on a spacecraft. We found that the SMM framework offers advantages to task performance and team efficiency due to its support of shared knowledge representations, however these benefits do not seem to reduce workload or improve other subjective measures. The significance of these findings for future space operations is discussed, as are directions for future research.
支持空间分布式人机协作的共享心智模型
有效的人机交互(HRI)是当前和未来空间作战的关键要求。然而,考虑到自主技术的局限性,机器人还无法在现实世界的任务约束下与人类船员协同工作。由于空间机器人操作固有的复杂性,机器人能够协调人机团队和手头任务的各个方面是至关重要的。在本文中,我们扩展了我们的共享心智模型(SMM)交互框架,以展示如何使用它来克服分布式HRI中固有的一些挑战,并促进空间机器人团队的协调。由于该框架尚未在实际系统中实现,因此我们进行了一项探索性研究,以确定SMM机制在涉及航天器上模拟自由飞行机器人助手的任务域中可以提供的潜在好处。我们发现,由于支持共享知识表示,SMM框架为任务绩效和团队效率提供了优势,但这些好处似乎并没有减少工作量或改善其他主观衡量标准。讨论了这些发现对未来空间操作的意义,以及未来研究的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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