基于COA优化算法的无人机多任务巡航路径规划研究

Wenjie Li, Shuncheng Cai, Hongjun Zheng
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引用次数: 1

摘要

针对无人机在三维不确定天气环境下的多任务巡航问题,提出了一种基于土狼优化算法的路径规划方法。首先,通过对云层动态变化的分析,构建了目的地风险评估模型,作为无人机在不确定天气环境下飞行的安全约束,然后对无人机多任务巡航问题进行了分析。为了使无人机巡航决策效益最大化,提出了一种无人机多任务巡航路径规划方法。最后,利用土狼优化算法根据飞行约束进行最优决策,并通过解码得到相应的路径坐标序列。仿真结果表明,该方法既能找到满足约束条件的路径,又能使惩罚代价最小化,从而保证无人机的飞行安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Multi-task Cruise Path Planning of UAV Based on COA Optimization Algorithm
Aiming at the multi-task cruising problem of UAV in three-dimensional uncertain weather environment, a path planning method based on coyote optimization algorithm is proposed in this paper. First of all, through the analysis of the dynamic changes of clouds, the destination risk assessment model is constructed as the safety constraint for UAV to fly in uncertain weather environment, and then the problem of UAV multi-task cruise is analyzed. a method of UAV multi-task cruise path planning is proposed to maximize the benefits of UAV cruise decision-making. Finally, the coyote optimization algorithm is used to make the optimal decision in line with the flight constraints, and the corresponding path coordinate sequence is obtained by decoding. The simulation results show that this method can find the path that satisfies the constraints and minimizes the penalty cost, so that the UAV can ensure the flight safety at the same time.
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