Human supervisors in multi-robot systems are primarily responsible for monitoring robots, but can also be assigned with secondary tasks. These tasks can act as interruptions and can be categorized as either intrinsic, i.e., being directly related to the monitoring task, or extrinsic, i.e., being unrelated. In this paper, we investigate the impact of these two types of interruptions through a user study ($N=39$), where participants monitor a number of remote mobile robots while intermittently being interrupted by either a robot fault correction task (intrinsic) or a messaging task (extrinsic). We find that task performance of participants does not change significantly with the interruptions but depends greatly on the number of robots. However, interruptions result in an increase in perceived workload, and extrinsic interruptions have a more negative effect on workload across all NASA-TLX scales. Participants also reported switching between extrinsic interruptions and the primary task to be more difficult compared to the intrinsic interruption case. Statistical significance of these results is confirmed using ANOVA and one-sample t-test. These findings suggest that when deciding task assignment in such supervision systems, one should limit interruptions from secondary tasks, especially extrinsic ones, in order to limit user workload.

翻译：在多机器人系统中，人类监督员主要负责监控机器人，但也可能被分配次要任务。这些任务可作为中断因素，可分为内在中断（即与监控任务直接相关）和外在中断（即与监控任务无关）。本文通过用户研究（N=39）探讨了这两类中断的影响：参与者需监控多台远程移动机器人，期间会间歇性地被机器人故障修正任务（内在中断）或消息传递任务（外在中断）打断。研究发现，参与者的任务绩效受中断影响不显著，但高度依赖于机器人数量。然而，中断会导致感知工作负荷增加，且外在中断在所有NASA-TLX量表维度上的工作负荷负面影响更为显著。参与者报告称，相较于内在中断，在外部中断与主任务之间切换的困难度更高。通过ANOVA和单样本t检验验证了上述结果的统计显著性。这些发现表明，在此类监督系统的任务分配决策中，应限制次要任务（尤其是外在中断）对主任务的干扰，以控制用户工作负荷。