HUNT让无人机在无定位条件下高速搜寻并实时追踪目标
HUNT: High-Speed UAV Navigation and Tracking in Unstructured Environments via Instantaneous Relative Frames
- 用即时相对帧统一导航与追踪，无需全局定位
- 实测在密林、集装箱区等复杂环境实现高速自主飞行
- 适合搜救、应急响应等无信号场景下的无人机应用
搜救任务要求无人机在未知非结构化环境中高速穿越并实时追踪目标。在感知受限且无全局定位的情况下同时实现这两项能力仍是开放挑战。现有相对导航方法通过将规划与控制锚定在可见目标上实现了鲁棒追踪，但无法在无目标可见时进行导航。本文提出HUNT（High-speed UAV Navigation and Tracking），一种实时统一的框架，将遍历、捕获与追踪整合为单一相对建模。HUNT直接基于机载即时观测量（如姿态、高度、速度）定义导航目标，支持搜索阶段的高响应性高速飞行。一旦检测到目标，相同的感知-控制流水线可无缝切换至追踪模式。在密集森林、集装箱场区及包含车辆和假人的真实搜救场景中进行的户外实验表明，该系统在全局方法失效时仍能实现鲁棒自主运行。
原文摘要 · Abstract (English)
Search and rescue operations require unmanned aerial vehicles to both traverse unknown unstructured environments at high speed and track targets once detected. Achieving both capabilities under degraded sensing and without global localization remains an open challenge. Recent works on relative navigation have shown robust tracking by anchoring planning and control to a visible detected object, but cannot address navigation when no target is in the field of view. We present HUNT (High-speed UAV Navigation and Tracking), a real-time framework that unifies traversal, acquisition, and tracking within a single relative formulation. HUNT defines navigation objectives directly from onboard instantaneous observables such as attitude, altitude, and velocity, enabling reactive high-speed flight during search. Once a target is detected, the same perception-control pipeline transitions seamlessly to tracking. Outdoor experiments in dense forests, container compounds, and search-and-rescue operations with vehicles and mannequins demonstrate robust autonomy where global methods fail.
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