Department of Automotive and Aeronautical Engineering, Loughborough University, Loughborough LE11 3TU, UK.
Sensors (Basel). 2018 Jul 3;18(7):2132. doi: 10.3390/s18072132.
In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wing aircraft surveys. This is achieved threefold: by the addition of wind to the survey flight time model, accounting for the fact fixed-wing aircraft are not constrained to flight within the polygon of the region of interest, and an intelligent method for decomposing the region into convex polygons conducive to quick flight times. It is shown that wind can make a huge difference to survey time, and that flying perpendicular can confer a flight time advantage. Small UAVs, which have very slow airspeeds, can very easily be flying in wind, which is 50% of their airspeed. This is why the technique is shown to be so effective, due to the fact that ignoring wind for small, slow, fixed-wing aircraft is a considerable oversight. Comparing this method to previous techniques using a Monte Carlo simulation on randomised polygons shows a significant reduction in flight time.
本文提出了一种新的规划固定翼无人机（UAV）航空勘测覆盖路径的方法。与之前文献中提出的更通用的覆盖路径规划技术不同，该方法特别专注于减少固定翼飞机勘测的飞行时间。这通过以下三种方式实现：在勘测飞行时间模型中添加风，考虑到固定翼飞机不受限于在感兴趣区域的多边形内飞行的事实，以及一种智能方法，将区域分解为有利于快速飞行时间的凸多边形。结果表明，风对勘测时间有很大影响，垂直飞行可以带来飞行时间优势。小型无人机的空速非常慢，很容易在风速为其空速的 50%的情况下飞行。这就是为什么该技术如此有效的原因，因为对于小型、慢速的固定翼飞机来说，忽略风是一个相当大的疏忽。通过对随机多边形进行蒙特卡罗模拟，将该方法与之前的技术进行比较，显示出飞行时间的显著减少。
