用混合现实沙盘实现无人机群的可视化监管，提升指挥效率。
FleetScape: A Mixed Reality Sandtable for Spatial Supervision and Control of Scalable Drone Fleets
- 将无人机群控制转化为空间交互，通过混合现实沙盘实时呈现任务与环境数据。
- 六名飞行员操作15架无人机时，系统显著提升态势感知与模式切换清晰度。
- 适合需要大规模无人机协同指挥的应急、巡检等场景，尤其关注人机协作设计。
随着自主无人机部署从单体向协同编队扩展，人类操作员的角色从直接驾驶转向高层监督。现有界面通常将多无人机控制简单类比为单机操作的放大。本文提出将无人机群监督重构为空间化交互，以更好应对复杂任务中的空间、时间与安全需求。我们开发了FleetScape——一个混合现实（MR）沙盘系统，可外显分层的实时任务、安全与环境数据，并支持手动干预与自主监督之间的流畅切换。构建了一个高保真建筑巡检仿真环境，生成并流式传输同步的多无人机与环境数据用于MR可视化。基于该原型，对六名经验丰富的无人机驾驶员进行了用户研究，使其管理最多15架无人机的集群。结果表明，FleetScape通过分层空间表征有效提升态势感知，并明确控制模式转换；但随着机群规模增大，态势感知能力出现瓶颈，导致监督策略分化。据此提炼出支持可扩展无人机群监管的设计启示。
原文摘要 · Abstract (English)
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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