多目标空地异构无人系统协同任务分配方法  

Collaborative Task Allocation Method for Multi-Target Air-Ground Heterogeneous Unmanned System

作　　者：范博洋 赵高鹏[1] 薄煜明[1] 吴祥 FAN Boyang;ZHAO Gaopeng;BO Yuming;WU Xiang(School of Automation,Nanjing University of Science and Technology,Nanjing 210094,Jiangsu,China)

机构地区：[1]南京理工大学自动化学院,江苏南京210094

出　　处：《兵工学报》2023年第6期1564-1575,共12页Acta Armamentarii

基　　金：国防基础科研计划项目(2019年)。

摘　　要：针对由地面无人车与多无人机组成的空地异构无人系统面向大范围、多目标的协同任务分配问题,以无人系统完成任务时间为优化目标,同时考虑无人机收放、续航能力以及任务时序等约束条件,建立空地异构无人系统的任务分配模型,提出一种多目标空地异构无人系统任务分配方法。结合密度值最大聚类和混合粒子群优化算法,对空地异构无人系统的任务分配问题进行求解,从而得到满足约束条件的全局任务分配结果;通过仿真实验对所提方法进行验证。实验结果表明,该方法能够有效地求解在不同作战环境中的空地异构无人系统的任务分配问题。To address the collaborative task allocation problem of air-ground heterogeneous unmanned systems composed of ground unmanned vehicles(UGV)and unmanned aerial vehicles(UAVs)facing large ranges and multiple targets,the task allocation model of air-ground heterogeneous unmanned systems is established with the completion time of the unmanned systems as the optimization goal and the constraints of the UAV launch and recovery,endurance and task sequence taken in account.A task allocation method for multi-target air-ground heterogeneous unmanned systems is proposed,which combines density peak clustering and hybrid particle swarm optimization algorithm(hybrid-PSO)to solve the task allocation problem of air-ground heterogeneous unmanned systems,so as to obtain the global task allocation results that satisfy the constraints.The proposed method is verified by simulation experiments,and the results show that the method can effectively solve the task allocation problem of air-ground heterogeneous unmanned systems in different operational environments.

关 键 词：无人系统 任务分配 密度值最大聚类 混合粒子群优化算法 

分 类 号：V279.2[航空宇航科学与技术—飞行器设计]