多机任务分配与路径规划协同优化法研究  

Research on Collaborative Optimization Method of Multi-UAV Task Allocation and Path Planning

作　　者：肖鹏[1] 谢锋 倪海鸿 张敏 汤志荔 李霓 Xiao Peng;Xie Feng;Ni Haihong;Zhang Min;Tang Zhili;Li Ni(School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China;Chengdu Aircraft Design and Research Institute,Aviation Industry Corporation of China,Chengdu 610091,China;Xi’an Key Laboratory of Intelligent Cognition and Control of Aircraft,Xi’an 710072,China)

机构地区：[1]西北工业大学航空学院,陕西西安710072 [2]中国航空工业集团公司成都飞机设计研究所,四川成都610091 [3]西安市飞行器智能认知与控制重点实验室,陕西西安710072

出　　处：《系统仿真学报》2024年第5期1141-1151,共11页Journal of System Simulation

基　　金：国家自然科学基金(62003272,62003266);特色学科基础研究(G2022WD)。

摘　　要：针对多无人机执行多目标协同侦察的任务需求,提出了多机多目标任务分配与路径规划的协同优化方法。以单亲遗传算法(partheno genetic algorithms,PGA)为基础,基于Dubins曲线构建了与实际路径代价相结合的代价函数;为进一步减小计算量,提出了基于无人机探测距离的聚类算法,将生成的聚类点作为无人机新的航路点。仿真结果表明:在考虑禁飞区域以及侦察点繁多情况下,该算法能够有效完成无人机的侦察任务分配并同时形成初步航路,提高了任务分配的合理性和收敛速度,并降低了全局代价。Aiming at the task requirements of multi-UAV to perform multi-target collaborative reconnaissance,a collaborative optimization method of multi-machine and multi-objective task allocation and path planning is proposed.Based on the partheno genetic algorithms(PGA),a cost function combined with the actual path cost is constructed through the Dubins curve.To further reduce the calculation cost,a clustering algorithm based on UAV detection distance is proposed,and the generated clustering point is used as a new waypoint of UAV.The simulation results show that considering the dangerous area and the large number of reconnaissance points,the algorithm can effectively complete the reconnaissance task allocation of the UAV and at the same time form a preliminary route.It improves the rationality and convergence speed of task assignment,and reduces the overall cost.

关 键 词：多机协同 单亲遗传算法 任务聚类 任务分配 航路规划 协同优化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]