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False alarm demand: A new metric for measuring robot performance in human robot teams

机译：假警报需求：用于在人体机器人团队中测量机器人性能的新度量

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Performance of robots in human robot teams has always been a topic of interest for many researchers in human robot interaction community. Traditionally adopted Crandall's model for performance measurements assume ideal conditions in which the operator switches control between robots sequentially based on acceptable performance level ignoring any false alarms due to erroneous interactions. In this paper, we present the false alarm demand, a new metric for measuring effects of false alarms on human robot team performance and extend the Crandall's model to situations in which false positives and false negatives are prevalent. Experiments were performed with real and virtual humanoid soccer robots across tele-operated, and point to point modes of autonomy. Measured false alarms demand and robot performances were largely consistent with the proposed extended Crandall's model predictions for both real and virtual experiments for both autonomy modes.
机译：人体机器人团队的机器人的表现一直是人类机器人互动界的许多研究人员感兴趣的话题。传统上采用的CrandAll的性能测量模型假设操作员根据可接受的性能水平顺序地切换机器人之间的控制，忽略由于错误的相互作用导致的任何误报。在本文中，我们展示了虚假警报需求，这是一种新的度量标准，用于测量虚假警报对人机团队性能的影响，并将Crandall模型扩展到虚假积极和假否定普遍存在的情况。通过远程操作的真实和虚拟人形足球机器人进行实验，并指向自主的点模式。测量的假警报需求和机器人性能在很大程度上与所提出的延长克兰德州的模型预测符合真实模式的实际和虚拟实验的模型预测。

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