期刊文献+

群机器人目标搜索中的通信模式研究 被引量:2

Communication Modes in Swarm Robotic Search for Target
下载PDF
导出
摘要 针对目标搜索过程中的群机器人协作问题,以扩展微粒群算法为建模工具和协调控制工具,比较研究同步和异步通信模式对搜索效率和系统能耗的影响。仿真结果表明,对于同等规模的群机器人系统,异步通信模式下的搜索效率比同步通信模式下高,能耗却比同步通信模式下低。因此,对于分布式协同的群机器人施加并发控制时,异步通信模式更为适合。 Aiming at the collaboration of swarm robots in target searching,with the extended particle swarm optimization method as modeling and coordination control tools,this paper introduces the influences of synchronous and asynchronous communication modes on working efficiency and energy consuming.Simulation results show that the asynchronous communication mode is predominated over its synchronous opponent in efficiency and energy consuming as to the same swarm size.Therefore,the asynchronous communication mode is more suitable for swarm robots working in distributive coordination manner.
出处 《太原科技大学学报》 2011年第4期264-268,共5页 Journal of Taiyuan University of Science and Technology
基金 国家自然科学基金(60975074) 山西省自然科学基金(2009011017-1) 山西高校科技研究开发项目(20091130) 太原科技大学博士启动基金(20102011)
关键词 群机器人 扩展微粒群算法 通信模式 搜索效率 swarm robots extended particle swarm optimization communication mode search efficiency
  • 相关文献

参考文献10

  • 1JAMES H, MICHAEL S. Multi-robot search using a physically-embedded Particle Swarm Optimization [ J ]. International Journal of Computational Intelligence Researoh,2008,4 (2) : 197-209.
  • 2NOUYAN S. Path Formation and Goal Search in Swarm Robotics [ R ]. Technical Report TR/IRIDIA/2004-14, Belgium:University Libre de Bruxelles,2004.
  • 3K SJO, DG LOPEZ, C PAUL, et al. Object Search and Localization for an Indoor Mobile Robot [ J]. Journal of Computing and Information Technology ,2009,17 ( 1 ) : 1-12.
  • 4PAUL E R, AMY L, HARINI V, MONICAL L, MARIA G. Communication strategies in Multi-Robot Search and Retrieval: Experiences with MinDART[ C ]//Proc Int'l Syrup on Distributed Autonomous Robotic Systems,2007:317-326.
  • 5职为梅,王芳,范明,杨勇.并行环境下的同步异步PSO算法[J].计算机技术与发展,2009,19(3):123-126. 被引量:2
  • 6陈保娣,曾建潮.异步随机微粒群算法[J].太原科技大学学报,2009,30(5):359-363. 被引量:2
  • 7曾建潮,薛颂东.群机器人系统的建模与仿真[J].系统仿真学报,2010,22(6):1327-1330. 被引量:5
  • 8J PUGI-I, A MARTINOLI. Inspiring and Modeling Multi-Robot Search with Particle Swarm Optimization [ C ]//Proceeding of the 4th IEEE Swarm Intelligence Symposium, USA: Hawaii Honolulu ,2007 : 1-5.
  • 9XUE S ,ZENG J. Controlling Swarm Robots for Target Search in Parallel and Asynchronously [ J]. International Journal of Modeling, Identification and Control, 2009,8 ( 4 ) : 353-360.
  • 10L BAYINDIR, E SSHIN. A Review of Studies in Swarm Robotics [ J ]. Turkish Journal of Electrical Engineering & Computer Sciences, 2007,15 (2) : 117-132.

二级参考文献20

共引文献6

同被引文献19

  • 1王旭阳,吕恬生,徐兆红,张培艳.类人机器人复杂运动的状态转换规划方法研究[J].中国机械工程,2007,18(6):659-662. 被引量:3
  • 2THRUN S. Robotic Mapping: A Survey [ R]. Technical Report CMU-CS-02-111. School of Computer Science Carnegie Mellon U-niversity Pittsburgh, USA,2002, :3-5.
  • 3BONABEAU ERIC, THERAULAZ GUY, DENEUBOURG JEAN—LOUIS. Fixed Response Thresholds and the Regulation of Division of Labor in Insect Societies[ J]. Bulletin of Mathematical Biology,1998,60:753-756.
  • 4SAHIN E. Swarm Robotics:From Sources of Inspiration to Domains of Application[ C]//Proc of the SAB Workshop on Swarm Robotics. Santa Monica, USA,2004 ; 10-20.
  • 5BALCH T. Hierarchic Social Entropy: An Information Theoretic Measure of Robot Group Diversity[ J]. Autonomous Robots,2000, 8(3):209-238.
  • 6王海.群机器人技术进展[C]//中国自动化学会第二十五届青年学术年会论文集,沈阳:东北大学出版社,2010:24.
  • 7XIE LIPING, TAN YING, ZENG JIANCHAO, et al. Artificial physics optimization:a brief survey [ J ]. International Journal of Bio- Inspired Computation ,2010,2 ( 5 ) :291-302.
  • 8XIE LIPING, TAN YING, ZENG JIANCHAO, et al. The convergence analysis of artificial physics optimisation algorithm [ J ]. Int. J. of Intelligent Information and Database Systems, 2011,5 (6) : 536 -554.
  • 9XIE LIPING, ZENG JIANCHAO, RICHARD A FORMATO. Convergence Analysis and Performance of the Extended Artificial Physics Optimization Algorithm [ J ]. Applied Mathematics and Computation, 2011,218:4000-4011.
  • 10XIE LIPING, ZENG JIANCHAO, CAI XINGJUAN. A Hybrid Vector Artificial Physics Optimization with Multi-Dimensional Search Method[ C ]//The 2nd International Conference on Innovations in Bio-inspired Computing and Applications( IBICA-2011 ) , Shenz- hen :2011.

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部