基于拥塞博弈的多无人机自主侦察任务规划  

Multi-UAV Autonomous Reconnaissance Mission Planning Based on Congestion Game

作　　者：赵玉亮 宋业新[1] 康丽文 Zhao Yuliang;Song Yexin;Kang Liwen(Department of Basic,Naval University of Engineering,Wuhan 430033,China;Marine Map Information Centre,Tianjin 300450,China)

机构地区：[1]海军工程大学基础部,武汉430033 [2]海图信息中心,天津300450

出　　处：《兵工自动化》2020年第7期45-51,共7页Ordnance Industry Automation

基　　金：国家自然科学基金羡慕(71171198)。

摘　　要：为解决通信中断时多无人机自主侦察任务规划的问题,提出一种基于拥塞博弈的分布式任务规划方法。根据问题场景给出各无人机的侦察收益函数以及各子区域的社会福利函数,基于拥塞博弈,建立多无人机自主侦察拥塞博弈模型,验证纯纳什均衡的存在性,给出多无人机自主侦察拥塞博弈的无政府状态代价和稳定状态代价的界限,设计一种具有性能保证并且易于实现的策略更新规则,并通过蒙特卡罗方法进行模拟仿真实验。仿真结果验证了该模型的适用性和策略更新规则的有效性。In order to solve the problem of autonomous reconnaissance mission planning of multi UAV when communication is interrupted,a distributed mission planning method based on congestion game is proposed.According to the problem scenario,the reconnaissance payoff function of each UAV and the social welfare function of each sub-region are given.Based on the congestion game,a congestion game model for autonomous reconnaissance of multi-UAV is established.Next,the existence of pure Nash equilibrium is verified.Give the boundary between the cost of anarchy and the cost of stable state of multi-UAV autonomous reconnaissance congestion game.Furthermore,a strategy updating rule with performance guarantee and easy implementation is designed and simulated by Monte Carlo method.Simulation results verify the applicability of the model and the validity of policy updating rules.

关 键 词：多无人机 自主侦察 通信中断 拥塞博弈 纳什均衡 无政府状态代价 稳定状态代价 策略更新规则 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]