Nowadays, it is quite common to have one unmanned aerial vehicle (UAV) working on a task but having a team of UAVs is still rare. One of the problems that prevent us from using teams of UAVs more frequently is flight planning. In this work, we present the first open-source solution (https://pypi.org/project/pode/) for splitting any complex area into multiple parts. The area of interest can be convex or nonconvex and can include any number of no-flight zones. Four solutions, based on the algorithm of Hert and Lumelsky, are tested with the aim of improving the compactness of the partitions. We also show how the shape of the partitions influences flight performance in a real case scenario.

如今，一种无人驾驶飞机（UAV）可以完成一项任务很普遍，但是拥有一支无人飞行器团队仍然很少见。阻碍我们更频繁地使用无人机团队的问题之一是飞行计划。在这项工作中，我们展示了第一个开源解决方案（https://pypi.org/project/pode/），用于将任何复杂区域划分为多个部分。感兴趣的区域可以是凸的或非凸的，并且可以包括任意数量的禁飞区。测试了四个基于Hert和Lumelsky算法的解决方案，目的是提高分区的紧凑性。我们还展示了在实际情况下隔板的形状如何影响飞行性能。