Generating Alerts to Assist With Task Assignments in Human-Supervised Multi-Robot Teams Operating in Challenging Environments

Abstract

In a mission with considerable uncertainty due to intermittent communications, degraded information flow, and failures, humans need to assess both the current and expected future states, and update task assignments to robots as quickly as possible. We present a forward simulation-based alert system that proactively notifies the human supervisor of possible, negatively-impactful events, which provides an opportunity for the human to retask agents to avoid undesirable scenarios. We propose methods for speeding up mission simulations and extracting alerts from simulation data in order to enable real-time alert generation suitable for time-critical missions. We present the results from a user trial and verify our hypothesis that the decision making performance of human supervisors can be improved by introducing forward simulation-based alerts.