面向多点侦察和通信服务的多无人机协同任务分配
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作者单位:

1.南京信息工程大学;2.桂林理工大学信息科学与工程学院;3.南京信息工程大学电子与信息工程学院

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基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目);中国博士后科学基金


Multi-UAV cooperative task allocation for multi-point reconnaissance and communication services
Author:
Affiliation:

1.Nanjing University of Information Science & Technology;2.Nanjing University of Information Science &3.amp;4.Technology;5.School of Information Science and Engineering, Guilin University of Technology;6.School of Electronics & Information Engineering, Nanjing University of Information Science & Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan);China Postdoctoral Science Foundation

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    摘要:

    针对多无人机对多个异构任务目标进行侦察和通信服务的协同优化问题,通过考虑不同目标的任务要求和价值,以及多机协同增益与任务行为制约关系,构建斯坦伯格博弈模型,将上层无人机建立为博弈领导者,下层无人机建立为博弈的跟随者,并提出一种分布式策略更新迭代算法,实现了多无人机任务分配方案的稳定收敛以及系统任务收益优化。仿真结果显示,所提方法能有效提升多无人机系统同时完成多个任务的效益,并能在不同环境下实现面向异构任务价值的高效协同。

    Abstract:

    Aiming at the collaborative optimization problem of multi-UAV reconnaissance and communication services for multiple heterogeneous targets, by considering the mission requirements and value of different targets, as well as the multi-UAV coordination gain and behavior restriction relationship, the Stackelberg game model is constructed. The upper-level drone is established as the leader of the game, the lower-level drone is established as the follower of the game, and a distributed strategy update iterative algorithm is proposed, which realizes the stable convergence of the multi-UAV task allocation scheme and the optimization of the task revenue. The simulation results show that the proposed method can effectively improve the efficiency of multi-UAV systems to complete multiple tasks at the same time, and can achieve efficient collaboration for the value of heterogeneous tasks in different environments.

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历史
  • 收稿日期:2021-08-16
  • 最后修改日期:2022-03-22
  • 录用日期:2022-03-26
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