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This paper introduces FleetScape, a Mixed Reality (MR) sandtable system designed to enhance the supervision and control of scalable drone fleets by reframing fleet management as a spatial interaction task. Through a high-fidelity building inspection simulation, the authors conducted a user study with experienced drone pilots, revealing that FleetScape improves situational awareness and facilitates smoother transitions between manual and autonomous control modes. However, the study also identified a diminishing situational awareness as fleet size increased, prompting the authors to derive design implications for future drone fleet supervision interfaces.
FleetScape reveals that spatial interaction can significantly enhance drone fleet supervision, but larger fleets may compromise situational awareness.
As autonomous drone deployments scale from individual units to coordinated swarms, the human operator's role shifts from direct piloting to high-level supervision. Current interfaces often treat multi-drone control as a scaled-up version of single-drone operation. We instead investigate how reframing fleet supervision as spatial interaction can better support the spatial, temporal, and safety demands of complex missions. We present FleetScape, a Mixed Reality (MR) sandtable system that externalizes layered real-time mission, safety, and environmental data while enabling fluid transitions between manual intervention and autonomous supervision. We developed a high-fidelity building inspection simulation that generates and streams synchronized multi-drone and environmental data for MR visualizations. We used this prototype to conduct a user study with six experienced drone pilots managing fleets of up to 15 drones. Our findings show that FleetScape supports situational awareness through layered spatial representations and clarifies control mode transitions. However, a limit to situational awareness was observed as fleet size increases, leading to different supervisory strategies. Finally, we derive design implications for supporting scalable drone fleet supervision.
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