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基于联盟形成博弈的异构无人机集群分布式任务分配算法

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针对无人机集群携带异构资源以及任务的异构需求下的复杂任务分配优化求解问题,提出一种基于联盟形成博弈的分布式任务分配算法。首先针对任务分配问题规模较大的特点以及资源的异构性,提出一种基于异构资源的改进K-medoids聚类算法,通过对无人机集群和任务进行聚类的预处理,降低了任务分配的规模和难度。考虑任务需求、机载资源以及路径成本等条件建立任务分配模型,将原有任务分配问题转化为联盟划分问题,设计了一种基于联盟形成博弈的分布式任务分配算法进行求解。最后,将30个具有异构需求的任务分配给100架携带3种异构资源的无人机的仿真结果表明,所提算法能够实现较好的任务分配效果,同时极大提高任务分配的实时性,充分发挥集群效能。
Distributed task allocation algorithm for heterogeneous unmanned aerial vehicle swarm based on coalition formation game
This paper presents a distributed allocation algorithm based on a coalition formation game to solve the complex task allocation problem when heterogeneous resources are carried by large-scale UAV swarm and tasks have heterogeneous requirements.Firstly,in response to the large scale of the cluster and the heterogeneity of resources,the K-medoids clustering method is improved by incorporating consideration of heterogeneous resources to reasonably reduce the scale of the original problem.Therefore,the allocation difficulty is reduced through preprocessing.Considering task requirements,resources carried by UAV,and path costs,a task allocation model is established and the original problem is transformed into a coalition partitioning problem.Then a distributed task allocation algorithm based on a coalition formation game is used to solve it.Finally,the simulation results of assigning 30 tasks with heterogeneous requirements to 100 unmanned aerial vehicles carrying 3 types of heterogeneous resources show that the proposed algorithm can improve the real-time performance of task allocation,reduce resource redundancy,and fully leverage cluster efficiency.

task allocationheterogeneous UAV swarmsheterogeneous resourcesclustering algorithmcoalition formation game

薛舒心、马亚杰、姜斌、李文博、刘成瑞

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南京航空航天大学自动化学院,南京 210016

飞行器自主控制技术教育部工程研究中心,南京 210016

北京控制工程研究所空间智能控制技术全国重点实验室,北京 100094

任务分配 异构无人机集群 异构资源 聚类算法 联盟形成博弈

2024

中国科学F辑
中国科学院,国家自然科学基金委员会

中国科学F辑

CSTPCD北大核心
影响因子:1.438
ISSN:1674-5973
年,卷(期):2024.54(11)