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Due to the potentially large number of units involved, the interaction with amulti-robot system is likely to exceed the limits of the span of apprehensionof any individual human operator. In previous work, we studied how this issuecan be tackled by interacting with the robots in two modalities --environment-oriented and robot-oriented. In this paper, we study how thisconcept can be applied to the case in which multiple human operators performsupervisory control on a multi-robot system. While the presence of extraoperators suggests that more complex tasks could be accomplished, littleresearch exists on how this could be achieved efficiently. In particular, onechallenge arises -- the out-of-the-loop performance problem caused by a lack ofengagement in the task, awareness of its state, and trust in the system and inthe other operators. Through a user study involving 28 human operators and 8real robots, we study how the concept of mixed granularity in multi-humanmulti-robot interaction affects user engagement, awareness, and trust whilebalancing the workload between multiple operators.

Improving Human Performance Using Mixed Granularity of Control in Multi-Human Multi-Robot Interaction