用无人机优化灾后侦察路径，提升覆盖范围与数据精度。
Optimizing the flight path for a scouting Uncrewed Aerial Vehicle
- 基于优化算法规划无人机最佳飞行高度与路径。
- 实现传感器覆盖面积最大、数据不确定性最小。
- 适用于灾后救援等复杂非结构化环境导航。
灾后场景具有高度非结构化特征，给救援车辆路径规划带来挑战。本文提出利用无人航空器（UAV）在该类环境中执行侦察任务。为此，我们设计了一种基于优化的方法，规划无人机在最优高度的飞行路径，使传感器能够覆盖最大区域，并以最低不确定性收集数据。
原文摘要 · Abstract (English)
Post-disaster situations pose unique navigation challenges. One of those challenges is the unstructured nature of the environment, which makes it hard to layout paths for rescue vehicles. We propose the use of Uncrewed Aerial Vehicle (UAV) in such scenario to perform reconnaissance across the environment. To accomplish this, we propose an optimization-based approach to plan a path for the UAV at optimal height where the sensors of the UAV can cover the most area and collect data with minimum uncertainty.
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