多无人机大面积协同区域覆盖路径规划

Furong Zhang, Xiaopan Zhang
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引用次数: 0

摘要

随着无人机技术的普及和发展,无人机覆盖路径规划问题也随之出现。本文提出了一种新的无人机覆盖路径规划问题模型,该模型采用多架无人机协同覆盖一定大面积,并考虑了覆盖过程中无人机对飞行距离、无人机能量补充和无人机能量回收的能量约束。在本文中,我们提出了一个两阶段的方法来解决这个问题。在第一阶段,我们提出了一种基于正则三角形网格的区域分解方法,将搜索区域转化为由节点和边组成的图。在第二阶段,我们使用混合线性整数规划(MILP)方法,基于第一阶段生成的图来规划覆盖路径。我们利用无人机自身的摄像头、速度、能量等实际参数对一个矩形区域进行解剖,并精确求解MILP模型,在求解过程中我们设计了三种不同的场景来验证模型的可行性和通用性,求解结果符合预期。我们还观察了UA V基地位置对求解速度的影响以及UA V飞行高度对模型求解目标值的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative Area Coverage Path Planning for Multiple UAVs Over Large Areas
With the popularity and development of Unmanned Aerial Vehicle (UAV) technology, the UAV coverage path planning problem has also emerged. In this paper, we propose a new model of UA V coverage path planning problem, which uses multiple UAVs to cover a certain large area cooperatively, and considers the energy constraint of UA Vs on flight distance, UA V energy replenishment and UA V recovery in the coverage process. In this paper, we propose a two-stage approach to solve the problem. In the first stage, we propose a region decomposition method based on a regular triangular grid, which converts the search region into a graph composed of nodes and edges. In the second stage, we use mixed linear integer programming (MILP) method to plan the coverage path based on the graph generated in the first stage. We use the actual parameters such as the drone's own camera, speed, energy, etc. to dissecte a rectangular area and accurately solve the MILP model, in the process of solving we designed three different scenarios to verify the feasibility and versatility of the model, and the solution results meet the expectations. We also observed the effect of UA V base location on the solving speed and the effect of UA V flight altitude on the model solving target value.
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