侦察用无人飞行器的飞行路径优化
Optimizing the flight path for a scouting Uncrewed Aerial Vehicle
AI总结：
针对灾后非结构化环境下救援车辆路径布设困难的问题，提出基于优化的侦察UAV路径规划方法，可在最优高度实现最大区域覆盖与最小不确定性的数据采集。
摘要：
灾后场景存在特殊的导航挑战，其中之一是环境的非结构化特性，这导致难以为救援车辆规划路径。本文提出在该类场景中使用无人飞行器（Uncrewed Aerial Vehicle，UAV）开展全域环境侦察，为此提出一种基于优化的方法，在最优高度为UAV规划路径，使UAV的传感器能够覆盖最大区域，并以最小不确定性收集数据。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
