利用草图地图先验实现室内无人机群有序导航
From Sketch Prior to Trajectories: A Mission-Oriented Coordinated Navigation Framework for Indoor UAV Swarm

- 基于平面草图地图构建任务导向的拓扑一致性表示
- 2D路径规划生成任务序列引导路径,3D优化生成无碰撞轨迹
- 支持有无通信条件下协同飞行,可扩展至多层建筑
面向室内巡检、安防巡逻和物流配送等任务,无人机群通常需按预定顺序访问特定区域。这些任务信息常来自部署前的草图地图先验(如平面图、CAD布局或疏散图)。尽管在三维空间中执行,但无人机通常在每层固定高度飞行,任务转移主要由平面连通性决定。本文提出一种任务导向的协同导航框架,利用草图地图先验,通过机载观测进行拓扑对齐,并将对齐后的先验与在线观测融合,构建任务导向的可通行性表示。进一步设计分层2D-3D协同导航框架:2D引导路径规划生成任务导向的引导路径,引导驱动的3D轨迹优化生成动态可行且无碰撞的轨迹。仿真与真实实验验证了该框架在结构化多房间室内环境中的有效性,并展示了在有/无通信条件下的协同导航能力。多楼层仿真结果表明系统可扩展至分层室内结构。
原文摘要 · Abstract (English)
UAV swarm for applications, such as indoor inspection, security patrol, and logistics delivery, are often mission-oriented rather than exploration-oriented. In these tasks, UAVs are required to visit task-relevant regions in a prescribed sequence, and such region-level mission information can often be obtained from pre-deployment sketch-map priors, such as floor plans, CAD layouts, or evacuation diagrams. Although these tasks are executed in three-dimensional space, UAVs usually fly within a specific altitude layer or a nearly fixed altitude range on each floor, making mission-level region transitions mainly governed by planar connectivity. Based on these observations, this paper proposes a mission-oriented coordinated navigation framework that exploits sketch-map priors for multi-UAV indoor operations. Onboard observations are used to perform topological alignment, and the aligned prior is fused with online observations to construct a mission-oriented traversability representation. A layered 2D--3D coordinated navigation framework is further developed, where 2D guided path planning generates mission-oriented guide paths and guide-driven 3D trajectory optimization produces dynamically feasible and collision-free trajectories. Simulation and real-world experiments validate the effectiveness of the proposed framework in structured multi-room indoor environments and further demonstrate its coordinated navigation capability under both communication-available and communication-loss conditions. Multi-floor simulation results show the scalability of the system to layered indoor structures.
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