期刊文献+

基于LSPI和滚动窗口的移动机器人反应式导航方法 被引量:6

A reactive navigation method of mobile robots based on LSPI and rolling windows
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摘要 结合最小二乘策略迭代(Least-squares policy iteration,LSPI)的算法特性和基于滚动窗口的实时重规划,提出一种新的基于LSPI和滚动窗口的反应式导航学习控制方法。仿真和实验结果表明:该方法对移动机器人在未知环境中的运动控制有效,并且对未知环境具有自适应性。 Combining the advantages of least-squares policy iteration(LSPI)and path planning based on rolling windows, a novel reactive navigation method based on LSPI,and rolling windows was presented.The results show that the proposed method is effective for reactive navigation of mobile robots in unknown environment and the adaptation for unknown environments of the proposed method is verified.
出处 《中南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2013年第3期970-977,共8页 Journal of Central South University:Science and Technology
基金 国家自然科学基金资助项目(61075072 90820302) 教育部新世纪优秀人才支持计划(NCET-10-0901)
关键词 移动机器人 反应式导航 增强学习 LSPI 滚动窗口 reactive navigation reinforcement learning LSPI rolling windows
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参考文献17

  • 1Faress K N, EL Hagry M T, EL Kosy A A. Trajectory tracking control for a wheeled mobile robot using fuzzy logic controller[J]. WSEAS Transactions on Systems, 2005, 4(7): 1017-1021.
  • 2Wang X, Hou Z, Zou A, et al. A behavior controller based on spiking neural networks for mobile robots[J]. Neurocomputing, 2008, 71(4/5/6): 655-666.
  • 3Er M J, Tan T P, Loh S Y. Control of a mobile robot using generalized dynamic fuzzy neural networks[J]. Microprocessors and Microsystems, 2004, 28(9): 491-498.
  • 4Busoniu L, Babuska R, de Schutter B. A comprehensive survey of multiagent reinforcement learning[J]. IEEE Transactions on Systems, Man and Cybernetics, 2008, 38 (2): 156-172.
  • 5Carrersa M, Yub J K, Batlle J, et al. Application of SONQL for real-time learning of robot behaviors[J]. Robotics and Autonomous System, 2007, 55 (8): 628-642.
  • 6Tan A H, Lu N, Xiao D. Integrating temporal difference methods and self-organizing neural networks for reinforcement learning with delayed evaluative feedback[J]. IEEE Transactions on Neural Networks, 2008, 19(2): 230-244.
  • 7徐听.增强学习与近似动态规划[M].北京:科学出版社,2010:15-35.
  • 8Xu X, Hu D W, Lu X C. Kernel based least-squares policy iteration[J]. IEEE Transactions on Neural Networks, 2007, 18 (4): 973-992.
  • 9Boubertakh H, Tadjine M, Glorennee P Y. A new mobile robot navigation method using fuzzy logic and a modified Q-learning algorithm[J]. Journal of Intelligent and Fuzzy Systems, 2010, 21(1/2): 113-119.
  • 10乔俊飞,樊瑞元,韩红桂,阮晓钢.机器人动态神经网络导航算法的研究和实现[J].控制理论与应用,2010,27(1):111-115. 被引量:6

二级参考文献11

  • 1BAUER A, WOLLHERR D, BUSS M. Human-robot collaboration: a survey[J]. International Journal of Humanoid Robotics, 2008, 5(1): 47 - 66.
  • 2JAN G E, CHANG K Y, PAR.BERRY I. Optimal path planning for mobile robot navigation[J]. IEEE-ASME Transactions on Mechatrioics, 2008, 13(4): 451 - 460.
  • 3BUSONIU L, BABUSKA R, DE SCHUTTER B. A comprehensive survey of multiagent reinforcement learning[J]. IEEE Transactions on Systems, Man and Cybernetics. 2008, 38(2): 156 - 172.
  • 4CARRERSA M, YUB J K, BATLLE J, et al. Application of SONQL for real-time learning of robot behaviors[J]. Robotics and Autonomous System, 2007, 55(8): 628 - 642.
  • 5ARLEO A, SMERALDI E GERSTNER W. Cognitive navigation based on nonuniform Gabor space sampling unsupervised growing networks and reinforcement learning[J]. IEEE Transactions on Neural Networks, 2004, 15(3): 639- 652.
  • 6MAX L, LIKHAREV K K. Global reinforcement learning in neural networks[J]. IEEE Transactions on Neural Networks, 2007, 18(2): 573 - 577.
  • 7TAN A H, LU N, XIAO D. Integrating temporal difference methods and self-organizing neural networks for reinforcementLeaming with delayed evaluative feedback[J]. IEEE Transactions on Neural Networks, 2008, 19(2): 230 - 244.
  • 8LEE J S, LEE H, KIM J Y, et al. Self-organizing neural networks by construction and pruning[J]. IEICE Transactions on Information & Systems, 2004, E87-D(11): 2489 - 2498.
  • 9席裕庚,预测控制,1993年
  • 10Tilove R B,Proc IEEE Conf Robotics and Automation Nice,1990年,566页

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