• 中国科技核心期刊
  • JST收录期刊
  • Scopus收录期刊

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于改进合同网算法的异构多AUV协同任务分配

李 娟 张昆玉

李 娟, 张昆玉. 基于改进合同网算法的异构多AUV协同任务分配[J]. 水下无人系统学报, 2017, 25(新刊5): 418-423. doi: 10.11993/j.issn.2096-3920.2017.05.004
引用本文: 李 娟, 张昆玉. 基于改进合同网算法的异构多AUV协同任务分配[J]. 水下无人系统学报, 2017, 25(新刊5): 418-423. doi: 10.11993/j.issn.2096-3920.2017.05.004
LI Juan, ZHANG Kun-yu. Heterogeneous Multi-AUV Cooperative Task Allocation Based on Improved Contract Net Algorithm[J]. Journal of Unmanned Undersea Systems, 2017, 25(新刊5): 418-423. doi: 10.11993/j.issn.2096-3920.2017.05.004
Citation: LI Juan, ZHANG Kun-yu. Heterogeneous Multi-AUV Cooperative Task Allocation Based on Improved Contract Net Algorithm[J]. Journal of Unmanned Undersea Systems, 2017, 25(新刊5): 418-423. doi: 10.11993/j.issn.2096-3920.2017.05.004

基于改进合同网算法的异构多AUV协同任务分配

doi: 10.11993/j.issn.2096-3920.2017.05.004
基金项目: 国家自然科学基金项目资助(51609046); 中央高校基本科研业务费专项资金资助(HEUCFM170403)
详细信息
    作者简介:

    李 娟(1976-), 女, 副教授, 主要研究方向为船舶智能控制.

  • 中图分类号: TJ630.1; TP242.6; TP393

Heterogeneous Multi-AUV Cooperative Task Allocation Based on Improved Contract Net Algorithm

  • 摘要: 传统合同网算法应用在异构多自主式水下航行器(AUV)协同任务分配时, 存在招标过程中多种招标者并存的情况, 不易产生有效招标者; 在投标过程中, 潜在投标者增加了无效投标数量及其招标者对投标结果的评估负担, 极易产生任务不合理的情况。针对以上2种问题, 文中提出了一种基于改进合同网算法的异构多AUV任务分配策略。该方法将任务负载率指标和令牌环网概念结合起来, 有效解决选择招标者及其任务不合理的问题。基于MATLAB的三维任务环境的仿真实验表明, 对于异构型多AUV进行任务分配, 文中提出的改进合同网算法能够有效提高整体效能并进行合理的任务分配。

     

  • [1] Choudhury B B, Biswal B B. Alternative Methods for Multi-robot Task Allocation[J]. Journal of Advanced Manufacturing Systems, 2011, 8(2): 163-176.
    [2] 赵敏. 分布式多类型无人机协同任务分配研究及仿真[D]. 南京: 南京理工大学, 2009.
    [3] Shima T, Rasmussen S J, Sparks A G, et al. Multiple Task Assignments for Cooperating Uninhabited Aerial Vehicles Using Genetic Algorithms[J]. Computers & Operations Research, 2006, 33(11): 3252-3269.
    [4] 寇英信, 王琳, 周中良. 多目标攻击条件下作战任务分配模型研究[J]. 系统仿真学报, 2008, 20(16): 4408- 4411.

    Kou Ying-xin, Wang Lin, Zhou Zhong-liang. Study of Combat Task Allocation Model in Multi-target Attack Condition[J]. Journal of System Simulation, 2008, 20(16) : 4408-4411.
    [5] 李炜, 张伟. 基于粒子群算法的多无人机任务分配方法[J]. 控制与决策, 2010, 25(9): 1359-1363.

    Li Wei, Zhang Wei. Method of Tasks Allocation of Multi-UAVs Based on Particles Swarm Optimization[J]. Control and Decision, 2010, 25(9): 1359-1363.
    [6] Nedjah N, Mendonc R M D, Mourelle L D M. PSO-based Distributed Algorithm for Dynamic Task Allocation in a Robotic Swarm[J]. Procedia Computer Science, 2015, 51(1): 326-335.
    [7] Polat K, Güne? S. A New Method to Forecast of Escherichia Coli Promoter Gene Sequences: Integrating Feature Selection and Fuzzy-AIRS Classifier System[J]. Expert Systems with Applications, 2009, 36(1): 57-64.
    [8] Owliya M, Saadat M, Jules G G, et al. Agent-Based Interaction Protocols and Topologies for Manufacturing Task Allocation[J]. IEEE Transactions on Systems Man & Cybernetics Systems, 2010, 43(1): 38-52.
    [9] Kim S K, Russell J S. Framework for an Intelligent Earthwork System: Part II. Task Identification/schedu- ling and Resource Allocation Methodology[J]. Automa- tion in Construction, 2003, 12(1): 15-27.
    [10] Hayano M, Dai H, Sugawara T. Role and Member Selection in Team Formation Using Resource Estimation for Large-scale Multi-agent Systems[J]. Elsevier Science Publishers B. V., 2014 , 146(C): 164-172.
    [11] Gerkey B P, Mataric M J. Sold!: Auction Methods for Multi Robot Coordination[J]. IEEE Transactions on Robotics and Automation, Special Issue on Multi-Robot Systems, 2002, 18(5): 758-768.
    [12] 李新亮, 翟江涛, 戴跃伟. 动态环境下基于改进合同网的多Agent任务分配算法[J]. 科学技术与工程, 2013, 13(27): 1671-1815.

    Li Xin-liang, Zhai Jiang-tao, Dai Yue-wei. A Task Allocation Algorithm Base on Improved Contract Net Protocol under the Dynamic Environment[J]. Science Technology and Engineering, 2013, 13(27): 1671-1815.
    [13] Smith R G. Thecntract Net Protocol High Level Communication and Control in Distributed Problem Solver[J]. IEEE Transaction on Computers, 1980, 29(12): 1104-1113.
    [14] 邸斌, 周锐, 丁全心. 多无人机分布式协同异构任务分配[J]. 控制与决策, 2013, 28(2): 274-278.

    Di Bin, Zhou Rui, Ding Quan-xin. Distributed Coordin- ated Heterogeneous Task Allocation for Unmanned Aerial Vehicles[J]. Control and Decision, 2013, 28(2): 274- 278.
    [15] 钱艳平, 夏洁, 刘天宇. 基于合同网的无人机协同目标分配方法[J]. 系统仿真学报, 2011, 23(8): 1672-1676.

    Qian Yan-ping, Xia Jie, Liu Tian-yu. Task Assignment Scheme Based on Contract Net[J]. Journal of System Simulation, 2011, 23(8): 1672-1676.
    [16] Ponda S S, Johnson L B, How J P. Distributed Chance-constrained Task Allocation for Autonomous Multiagent Teams[C]//American Control Conference. Piscataway. USA: IEEE, 2012.
    [17] Liang H, Kang F. A Novel Task Optimal Allocation Approach Based on Contract Net Protocol for Agentoriented UUV Swarm System Modeling[J]. Optik-International Journal for Light and Electron Optics, 2016, 127(8): 3928- 3933.
    [18] Valentinis F, Donaire A, Perez T. Energy-based Guidance of an Underactuated Unmanned Underwater Vehicle on A Helical Trajectory[J]. Control Engineering Practice, 2015, 44(13): 138-156.
  • 加载中
计量
  • 文章访问数:  687
  • HTML全文浏览量:  37
  • PDF下载量:  416
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-05-13
  • 修回日期:  2017-06-08
  • 刊出日期:  2017-12-20

目录

    /

    返回文章
    返回
    服务号
    订阅号