基于协同进化算法多无人机协同路径规划研究  

Research on Collaborative Path Planning for Multi-UAV Systems Based on Co-evolutionary Algorithm

作　　者：屈高敏 夏宗德 李继广 谭健 QU Gaomin;XIA Zongde;LI Jiguang;TAN Jian(School of Aircraft Engineering,Xi′an Aeronautical Institute,Xi′an 710077,China)

机构地区：[1]西安航空学院飞行器学院,西安710077

出　　处：《西安航空学院学报》2024年第3期1-9,共9页Journal of Xi’an Aeronautical Institute

基　　金：通用航空工程技术中心基金(XHY-2016084);陕西省自然科学基础研究计划资助项目(2023-JC-QN-0031);专业课程思政(23JXGG23604);陕西省科技厅各类计划重点项目(2022JZ-37)。

摘　　要：为了规划多无人机协同路径,提出一种协同进化算法。首先,生成预选路径,然后,求解协同函数和相关变量,对路径进行优化。该过程的主要目标是在特定威胁水平下找到最优协同路径和飞行速度,以最小化整体威胁代价。该方法综合考虑了多无人机之间的相互作用及外部环境因素,确保执行任务的高效性和安全性。在不同环境(包括二维和三维空间)和不同起飞时间间隔下进行仿真。结果显示,该方法在多种复杂条件下均表现出良好的适应性和有效性。该方法可以较好地解决复杂环境中多无人机协同执行任务时面临的挑战,为未来相关技术的发展和应用奠定基础。In order to plan the cooperative paths for multi-UAVs(unmanned aerial vehicles),a co-evolutionary algorithm is proposed.Initially,a preliminary path is generated,followed by solving for the synergy function and related variables to optimize the path.The primary goal of this process is to identify the optimal cooperative path and flight speed at a given threat level,aiming to minimize the overall threat cost.This approach comprehensively factors in the interactions among multiple drones and external environmental factors,ensuring efficient and safe task execution.Simulations are conducted across various environments,including 2D and 3D spaces,and with different takeoff time intervals.The results demonstrate that the method demonstrates excellent adaptability and effectiveness under diverse complex conditions.This method can effectively address the challenges encountered by multi-UAVs when executing collaborative tasks in complex environments,and lay a foundation for the development and application of related technologies in the future.

关 键 词：无人机 协同路径规划 协同进化法 

分 类 号：V279[航空宇航科学与技术—飞行器设计] V249[自动化与计算机技术—控制理论与控制工程] TP18[自动化与计算机技术—控制科学与工程]