TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human--Drone Teams

The availability of sensor-rich smart wearables and tiny, yet capable, unmanned vehicles such as nano quadcopters, opens up opportunities for a novel class of highly interactive, attention-shared human--machine teams. Reliable, lightweight, yet passive exchange of intent, data and inferences within such human--machine teams make them suitable for scenarios such as search-and-rescue with significantly improved performance in terms of speed, accuracy and semantic awareness. In this paper, we articulate a vision for such human--drone teams and key technical capabilities such teams must encompass. We present TagTeam, an early prototype of such a team and share promising demonstration of a key capability (i.e., motion awareness).

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