伴随着城市化进程的迅速发展, 无论在作战中还是民用, 都对无人机自主协同能力提出了新的要求。以城市环境为背景, 以无人机任务规划为研究对象, 针对目前无人机任务规划算法普遍较为复杂、实时性较差的问题, 提出一种新颖的任务规划算法。首先对城市中的建筑物建立简单的数学模型, 针对模型的特点使用了改进通视图法计算出所有最短路径, 然后使用背包算法完成任务分配。仿真结果表明该算法规划准确, 满足实时性要求。

The rapid development of urbanization presents new requirements to autonomous collaboration capability of UAVs both in military and civilian application.Considering that the current mission planning algorithms for UAVs have the drawbacks of high complexity and poor real-time performance, we proposed a novel UAV mission planning method based on urban environment.Simple mathematical models were created for the urban buildings at first.Then, the improved visibility graph was applied to create all the shortest paths based on the models, and knapsack problem algorithm was used to allocate the missions.Simulations show that the algorithm can make an accurate planning that satisfies the real-time requirements.