华南理工大学学报(自然科学版)

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考虑任务优先级的多无人机三维航迹协同规划模型和算法

孙博1 章文鹏1,2 魏明1,3   

  1. 1.中国民航大学 空中交通管理学院,天津 300300;

    2.西安交通大学 软件学院,陕西 西安 710049;

    3. 中国民用航空飞行学院 民航飞行技术与飞行安全重点实验室,四川 广汉 618300

  • 发布日期:2026-01-23

Multi-UAV 3D Trajectory Collaborative Planning Model and Algorithm Considering Task Priority

SUN Bo1 ZHANG Wenpeng1,2 WEI Ming1,3   

  1. 1. College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China;

    2. School of Software Engineering, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China;

    3. Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan 618300, Sichuan, China

  • Published:2026-01-23

摘要:

根据不同无人机的起讫点和计划出发时间,考虑时-空冲突、限制区空间分布、无人机性能等因素,建立一种考虑任务优先级的多无人机三维航迹协同规划模型,追求航迹长度成本和延误时间成本最少。设计求解该模型的多策略徒步优化算法,利用Logistic-Cubic混合映射进行种群初始化,在算法的探索阶段融合黄金正弦策略、开发位置更新策略对个体扰动以避免算法局部收敛现象,使用徒步旅行者交互寻找捷径策略以加快算法收敛能力。比较本文算法与其他5种经典算法求解12个基准测试函数的性能差异,并进行其改进策略的消融实验,从而验证该算法的可行性。最后,以某真实场景的无人机路径规划为例,剖析有、无推迟时间、任务优先级和时空冲突对调度结果的影响,并进一步比较这些算法的求解性能。研究表明:(1)虽然本模型比传统模型的总飞行时间、延误时间和里程分别增加0.8%、12.6%和1.7%,但是更加符合实际;(2)本文算法的解质量比HOA、DBO、GWO、PSO和SSA分别减少56.4%、82.4%、46.5%、91.9%和81.4%,其收敛性比它们也分别减少38.6%、86.1%、83.3%、48.4%和69.2%。

关键词: 多无人机, 三维航迹协同规划, 任务优先级, 徒步优化算法, 多策略

Abstract: According to the starting and ending points and planned departure time of different UAVs, a 3D track collaborative planning of multi-UAV considering task priority is established by considering time-space conflict, spatial distribution of restricted area, performance of UAVs and other factors. The objective is to minimize the total cost of trajectory length and delay time. A multi-strategy hiking optimization algorithm is designed to solve the model. Among them, a Logistic-Cubic hybrid mapping is used to initialize the population, a golden sinusoid strategy is integrated in the exploration phase of the algorithm, a position update strategy is developed to disturb individuals to avoid local convergence of the algorithm, and a hiker interaction strategy is used to find a shortcut to accelerate the convergence of the algorithm. The performance of the proposed algorithm is compared with other 5 classical algorithms to solve 12 benchmark functions, and the ablation experiment of its improved strategy is carried out to verify the feasibility of the proposed algorithm. Finally, taking the path planning of UAV in a real scene as an example, the influence of proposed model with and without delay time, task priority and spatio-temporal conflict on the scheduling results is analyzed. The solution performance of these algorithms is further compared to prove the superiority of our model and algorithm. The results show that: (1) compared with the traditional model, the total flight time, delay time and mileage of the proposed model are increased by 0.8%, 12.6% and 1.7% respectively, but it is more realistic; (2) The solution quality of proposed algorithm is 56.4%, 82.4%, 46.5%, 91.9% and 81.4% lower than that of HOA, DBO, GWO, PSO and SSA respectively, and its convergence is also 38.6%, 86.1%, 83.3%, 48.4% and 69.2% lower than that of them respectively.

Key words: multi-UAV, three-dimensional track collaborative planning, task priority, hiking optimization algorithm, multi-strategy