On the Impact of Interruptions During Multi-Robot Supervision Tasks

TL;DR

This study examines how intrinsic and extrinsic interruptions affect human supervisors monitoring multiple robots, revealing that extrinsic interruptions increase perceived workload and switching difficulty, though task performance remains unaffected.

Contribution

It provides empirical evidence on the differential impact of intrinsic versus extrinsic interruptions in multi-robot supervision, highlighting workload implications.

Findings

Interruptions increase perceived workload, especially extrinsic ones.

Task performance remains stable despite interruptions.

Extrinsic interruptions cause more difficulty in task switching.

Abstract

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.