[1]曹 雷,谭何顺,彭 辉,等.一种多UAV混合动态任务分配方法[J].南京理工大学学报(自然科学版),2015,39(02):206-214.
 Cao Lei,Tan Heshun,Peng Hui,et al.Mixed dynamic task allocation for multiple UAV[J].Journal of Nanjing University of Science and Technology,2015,39(02):206-214.
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一种多UAV混合动态任务分配方法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
39卷
期数:
2015年02期
页码:
206-214
栏目:
出版日期:
2015-04-30

文章信息/Info

Title:
Mixed dynamic task allocation for multiple UAV
作者:
曹 雷1谭何顺1彭 辉1潘明聪2
1.解放军理工大学 指挥信息系统学院,江苏 南京 210007; 2.南京陆军指挥学院 作战实验中心,江苏 南京 210045
Author(s):
Cao Lei1Tan Heshun1Peng Hui1Pan Mingcong2
1.College of Command Information System,PLA University of Science and Technology,Nanjing 210007,China; 2.Combat Experimental Center,Nanjing Army Command College of the PLA,Nanjing 210045,China
关键词:
动态任务分配 粒子群改进鱼群算法 分布式拍卖算法 状态信息
Keywords:
dynamic task allocation particle swarm optimizer-fish swarm algorithm decentralized auction algorithm state information
分类号:
TP301
摘要:
该文研究了战场环境下突发新任务的多无人机(UAV)动态任务分配问题,围绕任务分配过程中的时间复杂度和通信复杂度要求,在对任务及无人机分组的基础上,建立了无人机及无人机组执行任务的状态信息描述模型。提出了一种多UAV混合动态任务分配方法,将原问题分解为分组级任务分配和组内成员级任务分配两个层次,分别采用改进的粒子群改进鱼群算法(PSO-FSA)和分布式拍卖算法进行求解。仿真实验表明,该文方法能够降低任务分配问题求解的规模,具有低时间复杂度和低通信复杂度的特点,是一种有效的动态任务分配方法。
Abstract:
For the dynamic task allocation problem of the multi-unmanned aerial vehicle(UAV)with unexpected new tasks appearing in battle field,in order to fulfill its time complexity and communication complexity requirement,a state information model of UAV and UAV groups based on the grouping of tasks and UAVs is presented.A mixed dynamic task allocation method is proposed to decompose the problem into the group-level task allocation and the agent-level task allocation,and to solve them by using particle swarm optimizer-fish swarm algorithm(PSO-FSA)and the distributed auction algorithm.The simulation experiment proves the effectiveness of the algorithm and it can reduce the size of the dynamic task allocation and lead to the reduction of the time complexity and the communication complexity.

参考文献/References:

[1] Li Changhe,Yang Shengxiang.An adaptive learning particle swarm optimizer for function optimization[A].Evolutionary Computation,2009.CEC'09[C].Trondheim,Norway:IEEE,2009:381-388.
[2]Cai H,Liu J,Chen Y,et al.Survey of the research on dynamic weapon-target assignment problem[J].Journal of Systems Engineering and Electronics,2006,17(3):559-565.
[3]Jevtic A,Gutiérrez A,Andina D,et al.Distributed bees algorithm for task allocation in swarm of robots[J].Systems Journal,IEEE,2012,6(2):296-304.
[4]陈志敏,薄煜明,吴盘龙,等.收敛粒子群全区域自适应粒子滤波算法及其应用[J].南京理工大学学报,2012,36(5):861-868.
Chen Zhimin,Bo Yuming,Wu Panlong,et al.Novel lanscape addptive particle filter algorithm based on convergent particle swarm and its application[J].Journal of Nanjing University of Science and Technology,2012,36(5):861-868.
[5]龙涛,陈岩,霍霄华,等.战场环境中多无人机动态任务调度[J].计算机工程,2007,33(19):36-38.
Long Tao,Chen Yan,Huo Xiaohua,et al.Dynamic tasks scheduling of multiple unmanned aerial vehicle in battlefield environment[J].Computer Engineering,2007,33(19):36-38.
[6]Wu Z,Xiao M,Jin B,et al.Dynamic task allocation based on distance of superior probability auction[J].Journal of Convergence Information Technology,2012,7(2):10-17.
[7]Zavlanos M M,Spesivtsev L,Pappas G J.The distributed auction algorithm for the assignment problem[A].The 47th IEEE Conference on Decision and Control,2008[C].Cancun,Mexico:IEEE,2008:1212-1217.
[8]Luo L,Chakraborty N,Sycara K.Multi-robot assignment algorithm for tasks with set precedence constraints[A].The 2011 IEEE International Conference on Robotics and Automation(ICRA)[C].Karlsruhe,Germany:IEEE,2011:2526-2533.
[9]Luo L,Chakraborty N,Sycara K.Competitive analysis of repeated greedy auction algorithm for online multi-robot task assignment[A].The 2012 IEEE International Conference on Robotics and Automation(ICRA)[C].Saint Paul,US:IEEE,2012:4792-4799.
[10]谭何顺,曹雷,彭辉.一种多无人机层次化任务分配方法[J].解放军理工大学学报(自然科学版),2014,15(1):18-24.
Tan Heshun,Cao Lei,Peng Hui.Method of multi-UAV hierarchical task allocation[J].Journal of PLA University of Science and Technology(Natural Science Edition),2014,15(1):18-24.
[11]段其昌,唐若笠,徐宏英,等.粒子群优化鱼群算法仿真分析[J].控制与决策,2013,28(9):1436-1440.
Duan Qichang,Tang Ruoli,Xu Hongying,et al.Simulation analysis of the fish swarm algorithm optimized by PSO[J].Control and Decision,2013,28(9):1436-1440.

备注/Memo

备注/Memo:
收稿日期:2014-03-08 修回日期:2014-07-08
基金项目:国家自然科学基金(61174198); 江苏省自然科学基金(BK2011120); 解放军理工大学预研基金(KYZYZLXY1210)
作者简介:曹雷(1965-),男,教授,主要研究方向:指控理论与技术,E-mail:Caolei.nj@163.com。
引文格式:曹雷,谭何顺,彭辉,等.一种多UAV混合动态任务分配方法[J].南京理工大学学报,2015,39(2):206-214.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2015-04-30