期刊文献+

面向分布协同控制研究的仿真环境设计与实现 被引量:1

Design and Implementation of Simulation Environment for Distributed Cooperation Control
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摘要 针对分布式系统,尤其是多机器人系统中协同控制问题的研究需要,提出了一种具有分层嵌套结构的多Agent仿真环境设计方案,以克服现有仿真环境存在的兼容性差和算法移植困难的问题。设计方案在系统总体结构中引入了层次多Agent的设计思想;在子系统中采用Acromovi结构框架设计;在个体Agent中采用了混合型的内部结构设计。具体应用于多机器人仿真环境设计中,通过不同的实验配置方案,逐步实现多机器人系统的虚拟仿真和半实物仿真。最终的多机器人编队控制实验表明了设计方案的有效性。 A layered and nested multi-agent simulation environment design was proposed for cooperation control study on distributed system, especially on a multi-robot system, in order to overcome the incompatibility and algorithm transplant problem in current simulation environment. In the design, a layered method was adopted in system framework, then an Acromovi framework was introduced in the subsystem design, and a hybrid construction was adopted in standalone agent design. By using the above scheme and different experimental configurations, the virtual simulation and HIL simulation of a multi-robot system were realized step-by-step. Finally, the feasibility of the scheme is validated by results of multi-robot formation control trials.
出处 《系统仿真学报》 CAS CSCD 北大核心 2009年第19期6039-6042,共4页 Journal of System Simulation
基金 霍英东青年教师基金优选资助课题(114005) 湖南省自然科学基金(07JJ3122) 国家自然科学基金(60774076)
关键词 多智能体 分布协同控制 Acromovi 多机器人 半实物仿真 multi-agent distributed cooperation control Acromovi multi-robot HIL Simulation
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参考文献12

  • 1Wei Ren, Nathan Sorensen. Distributed coordination architecture for multi-robot formation control [J]. Robotics and Autonomous Systems (S0921-8890), 2007, 56(4): 324-333.
  • 2Terry L Huntsberger, Ashitey Trebiollennu, Hrand Aghazarian, et al. Distributed Control of Multi-Robot Systems Engaged in Tightly Coupled Tasks [J]. Autonomous Robots (S0929-5593), 2004, 17(1): 79-92.
  • 3Zichao Wang. A Critical Study of Multi-Agent Systems: Models, Architectures and Applications [D]. Montreal, Quebec, Canada: Concordia University, 2003.
  • 4Nathan Wiebe. Developing Grounded Communication in MultiAgent Systems [D]. Winnipeg, Manitoba, Canada: University of Manitoba, 2006.
  • 5Krzysztof Skrzypczyk. On Multi-Agent Coordination in the Presence of Incomplete Information [J]. Artificial Intelligence and Soit Computing-ICAISC2008 (S0302-9743), 2008, 5097/2008: 1254-1265.
  • 6Stewart Tansley. Microsoft Robotics Studio in Education [R]//RSS Workshop on Research in Robots for Education, Atlanta, GA, USA, June 2007.
  • 7Yoichiro Endo. User Manual for Mission Lab (V 7.0.). [K]. Atlanta, GA30332, USA: Georgia Tech Mobile Robot Laboratory, College of Computing, Georgia Institute of Technology, July 12, 2006.
  • 8舒文杰,耿丽娜,郑志强.RoboCup仿真研究[J].系统仿真学报,2004,16(10):2220-2222. 被引量:4
  • 9Balch, T. TeamBots2.0e [Z]. (2000-4). www.teambots.org.
  • 10Patricio Nebot, Enric Cervera. Agent-based Application Framework for Multiple Mobile Robots Cooperation [C]// Proceedings of the 2005 IEEE ICRA, Spain, 2005. USA: IEEE, 2005: 1509-1514.

二级参考文献13

  • 1[1]Itsuki Noda et al. Soccer Server Manual, RoboCupFederation [EB/OL]. http://www.robocup.org.
  • 2[2]Peter Stone. Layered Learning in Multi-agent System [D]. PHD dissertation, school of computer science, CMU, 1998.
  • 3[3]Jan Wendler, Hans-Dieter, Burkhard, Pascal Gugenberger, et al. AT Humboldt in RoboCup-98 (Team description) [A]. To appear in RoboCup-98 (Springer).
  • 4[4]Shi Li, Zhen Ye, Zengqi Sun. A New Agent Architecture for RoboCup Tournament: Cognitive Architecture [A]. In Proc. World Congress on Intelligent Control and Automation, 2000, 199-202.
  • 5[5]Jinyi Yao, Jiang Chen, Zengqi Sun. An application in RoboCup combining Q-learning with Adversarial Planning [A]. In The World Congress on Intelligent Control and Automation (WCICA'02), 2002.
  • 6[6]Remco de Boer, Jelle R.Kok. The Incremental Development of a Synthetic Multi-Agent System: The UvA Trilearn 2001 Robotic Soccer Simulation Team [D]. Master's thesis, University of Amsterdam, The Netherlands, February 2002.
  • 7[7]Peter Stone, Patrick Riley, Manuela Veloso. Defining and Using Ideal Teammate and Opponent Agent Models [A]. In Proc. of the twelfth Annual Conference on innovative Applications of Artificial Intelligence, 2000.
  • 8[8]Timo Steffens. Feature-based declarative opponent-modelling in multi- agent system [D]. Master's thesis, Institute of Cognitive Science Osnabrück, 2002.
  • 9[9]Peter Stone, David McAllester. An Architecture for Action Selection in Robotic Soccer [A]. In Proceedings of the Fifth International Conference on Autonomous Agents, 2001.
  • 10[10]Riedmiler M, Merke A, Meier D, Hoffmann A, Sinner A, Thate O, Ch.Kill, R Ehrmann. Karlsruhe Brainstormers-A Reinforcement Learning approach to robotic soccer [A]. In RoboCup-2000.

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