用于危险品检测的移动机械手的运动性能分析及其控制
|
摘要
由于化学危险品泄漏的危害性,各类化学反应容器和输送管道的泄漏检测与维修已经成为石化工业安全生产、预防重大事故发生所关注的问题。在危险环境中,具有自主能力的移动机械手便成为代替和辅助人类完成一定任务的最佳选择。本文在国家863计划项目“化学危险反应器泄漏检测与修补移动机械手系统”(项目编号:2003AA421040)的支持下,针对所研制的P3-AT型移动机械手进行了运动学、动力学分析,采用人工神经网络研究了移动机械手的运动控制技术。主要的研究内容与创新如下:
1、描述了所设计的P3-AT型移动机械手的基本结构特征,分析了五自由度机械手和两自由度轮式移动载体(平台)的运动特点。分别建立了移动载体子系统、机械手子系统以及移动机械手系统整体的运动学模型,进行了正、逆运动学分析。在ADAMS分析软件中建立了机械手的虚拟样机,分析了机械手的工作空间和特殊工作位置,得到了机械手实际应用中的有效工作区域。
2、根据移动机械手系统的复杂性,提出了运动规划策略,构建了简化的移动机械手系统结构模型,利用牛顿——欧拉方法推导了简化移动机械手系统的动力学模型。通过仿真分析了移动平台与机械手间的动力耦合作用,仿真表明移动平台的加速度值愈大,其对机械手关节负载力矩的影响愈大,并影响移动机械手的轨迹跟踪和定位精度。建立了移动平台子系统、机械手子系统的动力学理论模型,并对各子系统的动力学进行仿真分析,得到了机械手各关节转矩与位姿的关系和机械手几个较危险位姿;对于移动平台,通过控制其左右前轮的驱动力矩,可以实现移动平台按给定的轨迹运动,同时也能实现移动平台方向角的改变。
3、提出了基于神经网络的移动机械手的分层递阶智能控制策略,采用三层控制实现移动机械手的部分或完全自主控制。决策层进行任务规划;处理层包括两个径向基函数(RBF)神经网络子控制器,分别对移动载体和机械手的动力学进行控制和补偿;执行层依据处理层输出的信息来独立控制各驱动电机,实现所需的运动。RBF神经网络子控制器应用李雅普诺夫稳定性设计方法,通过分别建立移动载体、机械手和移动机械手系统的李雅普诺夫方程,由第二类李雅普诺夫方法建立了移动载体和机械手的动力学补偿,并应用Matlab对所建立的RBF网络进行训练仿真,仿真结果表明了RBF神经网络的有效性和可靠性。
4、针对移动机械手硬件体系结构进行了设计,其中包括移动载体、五自由度机械手,视觉CCD传感器和超声传感器模块等。介绍了移动机械手的控制软件设计,包括PMAC上运行的运动程序和移动载体PC上运行的主控程序。应用Matlab编程软件对五自由度机械手的运动及控制进行了仿真,验证了机械手操作的运动准确性。并在实验环境下对移动机械手系统进行了实验,验证了移动机械手运动的准确性及控制的有效性和可靠性。
Due to the harmfulness of deleterious chemistry leakage, the measurement and maintenance of chemistry reactors and carrying pipeline has arosed the attention of researchers. The mobility and manipulation capability of a mobile manipulator provides convenience to accomplish some tasks in dangerous environment. This dissertation is carried on the research to the dynamics and control technology for the mobile manipulator designed, supported by the China National Hi-tech R&D Program (863 Program)—Study on the mobile manipulator for measurement and maintenance of chemistry reactors (Granted No.2003AA421040).
1. The structure of P3-AT mobile manipulator designed is described. The kinematics character of 2 DOF mobile platform and 5 DOF manipulator is analyzed. The kinematics modeling of mobile platform and manipulator is studied respectively, then the kinematics modeling of mobile manipulator system is derived. And the forward and inverse kinematics equations are derived. Based on the research above, the simulation model of 5 DOF manipulator is developed in the software ADAMS, which can be used to analyze motion space and dynamics visually.
2. The strategy of coordination-motion planning for the mobile manipulator is presented, and a simple mechanism system model of the mobile manipulator is built. Then the dynamic modeling of the system is studied through the method of Newton-Euler. By dynamic computer simulation, the interaction between mobile platform and manipulator is analyzed. The analysis result indicated that the larger is the acceleration of mobile platform, the larger the force of manipulator applied by the platform is. It is harmful effects for position accuracy of mobile manipulator. And the theoretical dynamic models of them are derived by the method of Newton-Eular and Lagrange separately. By the computer simulation, dynamic characteristic of two subsystem is analyzed. The relation between joint moment and posture of manipulator is displayed, and the bad postures of manipulator are obtained. The mobile platform may achieve motion trace and alter azimuth as demand.
3. Based on the kinematic and dynamic motioned above, a hierarchical intelligent controller based on neural network is proposed for the coordinated control of the mobile manipulator, which mimics human behavior. It consists of three levels: decision-making level, processing level and execution level. Decision-making level is a task-planning unit. Processing level includes two RBF neural network controllers, in which unknown mobile platform and manipulator dynamic parameters are identified and compensated. Execution level controls the movement of each motor of mobile manipulator, based on the output control torques from processing level. In RBF neural network controllers, generalized Lyapunov equations of two subsystem (mobile platform and manipulator) and mobile manipulator system are derived, using Lyapunov stability theory. Then the simulation of sample training in RBF neural network is completed by Matlab software. The result shows the training in RBF neural network is effective and reliable.
4. The hardware system of the mobile manipulator is designed. It includes a mobile platform and a 5 DOF manipulator, CCD sensors and ultrasonic sensors module, etc. The control program of mobile manipulator is developed, including movement program in PMAC and central control program in PC of the mobile platform. Then the motion and control simulation of manipulator is completed by Matlab software, which displays the action accuracy of manipulator. In the end, a experiment of mobile manipulator is accomplished. The experiment and simulation results show that kinetic control of manipulator is precise and reliable.
1、描述了所设计的P3-AT型移动机械手的基本结构特征,分析了五自由度机械手和两自由度轮式移动载体(平台)的运动特点。分别建立了移动载体子系统、机械手子系统以及移动机械手系统整体的运动学模型,进行了正、逆运动学分析。在ADAMS分析软件中建立了机械手的虚拟样机,分析了机械手的工作空间和特殊工作位置,得到了机械手实际应用中的有效工作区域。
2、根据移动机械手系统的复杂性,提出了运动规划策略,构建了简化的移动机械手系统结构模型,利用牛顿——欧拉方法推导了简化移动机械手系统的动力学模型。通过仿真分析了移动平台与机械手间的动力耦合作用,仿真表明移动平台的加速度值愈大,其对机械手关节负载力矩的影响愈大,并影响移动机械手的轨迹跟踪和定位精度。建立了移动平台子系统、机械手子系统的动力学理论模型,并对各子系统的动力学进行仿真分析,得到了机械手各关节转矩与位姿的关系和机械手几个较危险位姿;对于移动平台,通过控制其左右前轮的驱动力矩,可以实现移动平台按给定的轨迹运动,同时也能实现移动平台方向角的改变。
3、提出了基于神经网络的移动机械手的分层递阶智能控制策略,采用三层控制实现移动机械手的部分或完全自主控制。决策层进行任务规划;处理层包括两个径向基函数(RBF)神经网络子控制器,分别对移动载体和机械手的动力学进行控制和补偿;执行层依据处理层输出的信息来独立控制各驱动电机,实现所需的运动。RBF神经网络子控制器应用李雅普诺夫稳定性设计方法,通过分别建立移动载体、机械手和移动机械手系统的李雅普诺夫方程,由第二类李雅普诺夫方法建立了移动载体和机械手的动力学补偿,并应用Matlab对所建立的RBF网络进行训练仿真,仿真结果表明了RBF神经网络的有效性和可靠性。
4、针对移动机械手硬件体系结构进行了设计,其中包括移动载体、五自由度机械手,视觉CCD传感器和超声传感器模块等。介绍了移动机械手的控制软件设计,包括PMAC上运行的运动程序和移动载体PC上运行的主控程序。应用Matlab编程软件对五自由度机械手的运动及控制进行了仿真,验证了机械手操作的运动准确性。并在实验环境下对移动机械手系统进行了实验,验证了移动机械手运动的准确性及控制的有效性和可靠性。
Due to the harmfulness of deleterious chemistry leakage, the measurement and maintenance of chemistry reactors and carrying pipeline has arosed the attention of researchers. The mobility and manipulation capability of a mobile manipulator provides convenience to accomplish some tasks in dangerous environment. This dissertation is carried on the research to the dynamics and control technology for the mobile manipulator designed, supported by the China National Hi-tech R&D Program (863 Program)—Study on the mobile manipulator for measurement and maintenance of chemistry reactors (Granted No.2003AA421040).
1. The structure of P3-AT mobile manipulator designed is described. The kinematics character of 2 DOF mobile platform and 5 DOF manipulator is analyzed. The kinematics modeling of mobile platform and manipulator is studied respectively, then the kinematics modeling of mobile manipulator system is derived. And the forward and inverse kinematics equations are derived. Based on the research above, the simulation model of 5 DOF manipulator is developed in the software ADAMS, which can be used to analyze motion space and dynamics visually.
2. The strategy of coordination-motion planning for the mobile manipulator is presented, and a simple mechanism system model of the mobile manipulator is built. Then the dynamic modeling of the system is studied through the method of Newton-Euler. By dynamic computer simulation, the interaction between mobile platform and manipulator is analyzed. The analysis result indicated that the larger is the acceleration of mobile platform, the larger the force of manipulator applied by the platform is. It is harmful effects for position accuracy of mobile manipulator. And the theoretical dynamic models of them are derived by the method of Newton-Eular and Lagrange separately. By the computer simulation, dynamic characteristic of two subsystem is analyzed. The relation between joint moment and posture of manipulator is displayed, and the bad postures of manipulator are obtained. The mobile platform may achieve motion trace and alter azimuth as demand.
3. Based on the kinematic and dynamic motioned above, a hierarchical intelligent controller based on neural network is proposed for the coordinated control of the mobile manipulator, which mimics human behavior. It consists of three levels: decision-making level, processing level and execution level. Decision-making level is a task-planning unit. Processing level includes two RBF neural network controllers, in which unknown mobile platform and manipulator dynamic parameters are identified and compensated. Execution level controls the movement of each motor of mobile manipulator, based on the output control torques from processing level. In RBF neural network controllers, generalized Lyapunov equations of two subsystem (mobile platform and manipulator) and mobile manipulator system are derived, using Lyapunov stability theory. Then the simulation of sample training in RBF neural network is completed by Matlab software. The result shows the training in RBF neural network is effective and reliable.
4. The hardware system of the mobile manipulator is designed. It includes a mobile platform and a 5 DOF manipulator, CCD sensors and ultrasonic sensors module, etc. The control program of mobile manipulator is developed, including movement program in PMAC and central control program in PC of the mobile platform. Then the motion and control simulation of manipulator is completed by Matlab software, which displays the action accuracy of manipulator. In the end, a experiment of mobile manipulator is accomplished. The experiment and simulation results show that kinetic control of manipulator is precise and reliable.
引文
1. Daily M. Autonomous Cross-Country Navigation With the ALV. IEEE Int Conf. Robotics and Automation, 1988:718-726.
2. 张明路,关柏青,丁承君.基于彩色视觉和模糊控制的移动机器人的路径跟踪.中国机械工程,2004,13(8):636-639.
3. 李丽宏.基于双目显微立体视觉系统的研究.河北工业大学学报,2003,31(6):21-24.
4. 罗荣海.基于平行接近法的对运动目标跟踪的研究. 机器人技术与应用,2001(6):25-27.
5. Triend E, Kringman D J. Stereo vision and navigation within buildings. IEEE Int Conf. Robotics and Automation, 1987:1725-1730.
6. 王建刚, 董再励, 徐心平. 遥控作业移动机器人环境方法研究. 机器人, 1997, 19(4):244-249.
7. 马兆青, 袁增任. 基于栅格方法的移动机器人实时导航和避障. 机器人, 1996, 18(6):344-348.
8. 马保离, 霍伟. 移动机器人的路径跟踪与镇定. 机器人, 1995, 17(6):358-362.
9. 日本机器人学会. 机器人技术手册. 北京:科学出版社, 1996.
10. Madarasz R L, Heing L C, Crimp R F et al. The design of autonomous vehicle for the disabled. IEEE Joint Robotics and automation, RA2, 1986:117-126.
11. Tillema H G. An overview of the mobile autonomous robot Twente Project, MART-93, Tmwente University, WA315, 1993:315-319.
12. Egeland O, Berglund E, Sordalen O J. Exponential stabilization of a nonholonomic underwater vehicle with constant desired configuration. Proc. IEEE Inter. Conf. On Robotics and Automation, 1994:1234-1245.
13. Sheng L. Robust and intelligent control of mobile manipulators. [Dissertation]. Toronto: University of Toronto, 2001.
14. Saeed B. Niku, Introduction to Robotics: Analysis, Systems, Application. USA:Pearson Education, 2001:1-154
15. Fred G. Martin.Robotic Explorations A Hands-on Introduction to Engineering. USA:Pearson Education ,Inc.,2004:1-263
16. 卢韶芳,刘大维.自主式移动机器人导航研究现状及其相关技术.农业机械学报, 2002, 33(2):112-116
17. 欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究.机器人,2000, 22(6):521-526
18. Triendl E, Kriegman D. Stereo vision and navigation within building. IEEE Int.Conf.Robotics and Automation, Raleigh, NC. 1987:1725-1730
19. Dickmanns E D, Zapp A. Autonomous high speed road vehicle guidance by computer vision. IFAC 10th World Congress, Munich, FRG,1988:221-226
20. Turk M A. Video road-following for the autonomous land vehicle. IEEE Int.Conf.Robotics and Automation, Raleigh, NC. 1987:1542-1547
21. Netra J, Tardos T D, Horn J et al. Fusion rang and intensity images for mobile robot location. IEEE Transactions on Robotics and Automation, 1999, 15(1):76-84
22. Everett C H R. Survey of collision avoidance and ranging sensors for mobile robots. Robotics and Autonomous Systems, 1989, 5(1):65-68
23. Tanner H G., Kyriakopoulos K J, Krikelis N I. Advanced agricultural robots: kinematics and dynamics of multiple mobile manipulators handling non-rigid material. Computers andElectronics in Agriculture, 2001, 31(5): 91-105
24. 王栋耀, 马旭东, 戴先中. 基于声纳的移动机器人沿墙导航控制. 机器人, 2004,(4):179-184
25. 孟江华, 朱纪洪, 孙增圻. 未知环境下基于传感器的移动机器人路径规划新方法. 机器人, 2005,(4):86-91
26. 付宜利, 顾晓宇, 王树国. 基于模糊控制的自主机器人路径规划策略研究. 机器人, 2004,(6):54-59
27. 王敏, 金波, 黄心汉. 基于传感器和模糊规则的机器人在动态障碍环境中的智能运动控制. 控制理论与应用, 2000,(6):124-129
28. 徐国华, 谭民. 移动机器人的发展现状及其趋势. 机器人技术与应用, 2001,(3):115-120
29. 王越超. 我国危险作业机器人研究开发取得新进展. 机器人技术与应用,2005,(6):11-14
30. 蔡自兴. 智能控制及移动机器人研究进展. 中南大学学报(自然科学版), 2005,(5):108-113
31. 王仁奎, 李仲男, 赵耀明等. 反恐战士----广州卫富机器人. 机器人技术与应用, 2003,(3):61-64
32. 胡传平. 消防机器人的开发与应用. 机器人技术与应用, 2003, (5):147-152
33. 陈亮, 杨汝清, 谢霄鹏. 基于视觉的高压带电清扫机器人瓷瓶自动定位伺服系统. 机器人, 2004, (2):134-139
34. 肖永利, 张琛. 微型飞行器的研究现状与关键技术. 宇航学报, 2001(5):38-42
35. Saeed B N. Scheme for active positional correction of robot arms. Proceedings of the International Conference on CAD/CAM, Robotics, and Factories of the Future, Columbia,1991:590-596
36. Fred G. Martin.robotic explorations a hands-on introduction to engineering. USA:Pearson Education ,Inc.,2004:1-263
37. 卢韶芳,刘大维.自主式移动机器人导航研究现状及其相关技术.农业机械学报, 2002,
33(2):112-116
38. 欧青立,何克忠. 室外智能移动机器人的发展及其关键技术研究. 机器人, 2000, 22(6):521-526
39. Yamamoto Y, Yun X P. Coordinating locomotion and manipulation of a mobile manipulator. Proceedings of the 31st Conference on Decision and Control[C]. Tucson,1992:2643-2648
40. Seraji H. Motion Control of mobile manipulators.Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Piscataway, 1993:2056-2063
41. Carriker W F, Khosla P K, Krogh B H. Path planning for mobile manipulators for multiple task execution. IEEE Transactions on Robotics and Automation, 1991, 7(30):403-408
42. 张硕生,余达太.轮式移动机械手的点—点运动规划方法.北京科技大学学报,2001,23(1):81-84
43. 张硕生,余达太.轮式移动机械手的多点运动规划方法.北京科技大学学报,2001,23(2):177-180
44. Foulon G, Fourquet J Y, Renaud M. Planning point-to-point paths for nonhonolomic mobile manipulators. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Victoria, Canada, 1998:374-379
45. Tchon K, Jakubiak J, Muazynski R . Regular jacobian motion planning algorithms for mobile manipulators . IFAC[C].2002
46. Tanner H G, Kyriakopoulos K J. Nonholonomic motion planning for mobile manipulators. Proceedings of IEEE International Conference on Robotics and Automation[C]. San Francisco, 2000:1233-1238
47. Akira M, Seiji F, Yamamoto M. Trajectory planning of mobile manipulator with end – Effector’s specified path. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Maui, Hawaii, 2001:2264-2269
48. Tan J D, Xi N. Unified model approach for planning and control of mobile manipulators.Proceedings of IEEE International Conference on Robotics and Automation[C]. Arlington, 2001:1-8
49. Huang Q, Tanie K, Sugano S. Coordinated motion planning for a mobile manipulator considering stability and manipulation. International Journal of Robotics Research, 2000,19(8):732-742
50. Yoshio Y, Yun X. Coordinating locomotion and manipulation of a mobile manipulator. IEEE Trasactions on Automatic Control, 1994, 39 (6): 1326-1332
51. Dubowsky S, Tanner A B. A study of the dynamics and control of mobile manipulators subjected to vehicle disturbances. In: Proceedings of 4th Int. Symp. of Robotics Research, Santa Cruz, CA. 1987: 111-117
52. Yamamoto Y, Yun X. A modular approach to dynamic modeling of a class of mobile manipulator. International Journal of Robotic and Automation, 1997, 12 (2): 41-48
53. Saha S K, Angeles J. Kinematics and dynamics of a three-wheeled 2-DOF AGV. Ieee Int. Conf. on Rob. & Autom., Piscataway, NJ, 1989, 3: 1572-1577
54. Qing Y, Chen I M. Variational-vector calculus formulation for dynamics of nonholonomic mobile manipulator system. IEEE International Conference on Robotics and Automation, Seoul,Korea, 2001: 216-226
55. 张硕生,余达太. 轮式移动操作机器人的动力学模型.北京石油化工学院学报,2002,10(2):22-27
56. 吴玉香,胡跃明. 轮式移动机械臂的建模与仿真研究. 计算机仿真,2006,23(1):147-151
57. Liu K, Lewis F L. Decentralized continuous robust controller for mobile robots. Proc. 1990 Int. Conf. obot. And Autom, Cincinnati, OH, May 1990:1822-1827
58. Yamamoto Y, Yun X. Control of mobile manipulators following a moving surface. In: International Conference of Robotics and Automation, Atlanta, GA, 1993, 3:1-6
59. Yamamoto Y, Yun X. Coordinating locomotion and manipulation of a mobile manipulator. Automation Control, 1996, 39(6): 1326-1332
60. Yamamoto Y, Yun X. Effect of the dynamic interaction on coordinated control of mobile manipulator. IEEE Transaction on Robotics and Automations, 1996, 12(5) :816-824
61. Wiens G J. Effects of dynamics coupling in mobile system. Proceedings of World Conference on Robotic Systems[C].1989:43-57
62. Wiens G J, Jang W M. Passive joint control of dynamic coupling in mobile robots. International Journal of Robotic Research, 1994,13(3):209-220.
63. Yamamoto Y, Yun X P. Control of mobile manipulators following a moving surface. Proceedings of IEEE International Conference on Robotics and Automation[C]. Piscataway, 1993:1-6
64. Lee H K, Takubo T, Arai H, et al. Control of mobile manipulators for power assist systems. Journal of Robotics Systems, 2000,17(9):469-477
65. Jagannathan S, Zhu S Q. Path planning and control of a mobile base with nonholonomic constraints. Robotica, 1994(12):529-540
66. Evangelos P, John P. Planning and model-based control for mobile manipulators. International Journal of Environment and Pollution, 2007(30)2:213-230
67. Liu K, Lewis F L. Decentralized continuous robust controller for mobile robots. Journal of Applied Mechanics, Transactions ASME, 2005(72)2: 306-308
68. Sheng L, Goldenberg A A. Robust damping control of mobile manipulators. IEEE Transactions on Systems, Man and Cybernetics, Part B, 2002, 32(1):126-132.
69. Sheng L, Goldenberg A A. Neural-network control of mobile manipulators. IEEE Transactions on Neural Networks, 2001, 12(5):1121-1133.
70. Chung J H, Velinsky Steven A, Hess R A. Interaction control of a redundant mobile manipulator. International Journal of Robotics Research, 1998, 17(12):1302-1309
71. Yamamoto Y, Yun X P. Coordinated obstacle of a mobile manipulator. Proceedings of IEEE International Conference on Robotics and Automation[C].1995:2255-2260
72. Ogren P, Egerstedt M, Hu X. Reactive mobile manipulation using dynamic trajectory Tracking. Proceedings of IEEE International Conference on Robotics and Automation[C]. San Francisco, 2000:3473-3478.
73. FU L P. An adaptive routing algorithm for in vehicle route guidance systems with real time information[J]. Transportation Research B, 2001, 35(8): 749-765
74. Dong WJ,Chou JM, Feng GL, Progress in the study of retrospective numerical scheme and the climate prediction, Acta Mechanica Sinica,2004,20(5):38-41
75. 董文杰,徐文立. 移动机械手的跟踪控制. 控制与决策,2001,16(6):914-917.
76. 董文杰,徐文立. 移动机械手的鲁棒控制. 控制理论与应用,2002,19(3):345-348
77. 董文杰,徐文立. 不确定非完整移动机械手的鲁棒控制. 清华大学学报,2002,42(9):1261-1264.
78. Jagannathan S. Discrete-time fuzzy logic control of a mobile robot with an onboard manipulators. International Journal of Systems Science, 1997, 28(12):1195-1209.
79. Kang S, Komoriya K, Yokoi K, et al. Reduced inertial effect in damping-based posture control of mobile manipulator. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 2001:488-493
80. Yamamoto Y, Yun X P. Effect of the dynamic interaction on coordinated control of mobile manipulators. IEEE Transactions on Robotics and Automation, 1996, 12(5):816-824
81. Ghasempoor S. A measure of stability for mobile manipulator. Proceedings of IEEE International Conference on Robotics and Automation[C]. 1995:2249-2254.
82. Rey D A, Papadopoulos E G. On-line automatic tipover for a mobile manipulator. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1997:1273-1278.
83. Yoneda. K. Tumble stability criterion of integrated locomotion and manipulation. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1996:870-876
84. Dubowsky S. Planning mobile manipulator motions considering vehicle dynamic stability constrains[A]. Proceedings of IEEE International Conference on Robotics and Automation[C]. 1989:1271-1276.
85. Sugano S. Stability control for mobile manipulator using potential method. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C].1994:839-846
86. Huang Q, Sugano S, Tanie K. Stability compensation of a mobile manipulator by manipulator motion: feasibility and planning. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1997:1285-1292
87. 马明山,朱绍文,何克忠.室外机器人定位技术研究. 电工技术学报,1998,13(2):43-46
88. 陈延国,于澎,高振东.自主移动机器人定位方法的研究现状. 应用科技, 2002,29(11):41-43
89. Rumelhart G A. Stable adaptive neuron-control design via Lyapunov function derivation estmation. Automatica, 2001,37(8):1213-1221
90. Lewis F L, Liu K, Yesildirek A. Neural net robot controller with guaranteed tracking performance. IEEE Transactions on Neural Networks, 1995,6(3):703-715
91. Lewis F L, Yesildirek A, Liu K. Multilayer neural net robot controller: structure and stability proofs. IEEE Transactions on Neural Networks, 1996,7(2):388-399
92. Chen F C, Khalil H K. Adaptive control of nonlinear continuous-time systems using neural networks. International Journal of Control, 1992, 55(6):1299-1317
93. Chen F C, Liu C C. Adaptively controlling nonlinear continuous-time systems using multilayer neural networks. IEEE Transactions on Automatic Control, 1994,39(6):1306-1310
94. Chen F C, Khalil H K. Adaptive control of a class of nonlinear discrete time systems using neural networks. IEEE Transactions on Automatic Control, 1995,40(5):791-801
95. Sanner R M, Slotine J J E. Stable adaptive control and recursive identification using radial gaussian networks. In: Proceedings of IEEE Conference on Decision and Control, Brighton, 1991:2116-2123
96. Sanner R M, Slotine J J E. Gaussian networks for direct adaptive control. IEEE Transactions on Neural Networks, 1992, 3(5):837-863
97. Sanner R M, Slotine J J E. Stable adaptive control of robot manipulators using neural networks. Neural Computation, 1995, 7(3):753-790
98. Sanner R M, Slotine J J E. Structurally dynamic wavelet networks for the adaptive control of uncertain robotic systems. In: Proceedings of the 34th IEEE Conference on Decision and Control, New Orleans, LA,1995:2460-2467
99. Polycarpou M M, Ioannou P S. Identification and control of nonlinear systems using neural network models: design and stability analysis. EE-Report 91-09-01, University of Southern California,1991
100.Polycarpou M M, Ioannou P A. Neural networks as on-line approximators of nonlinear systems. In: Proceedings of IEEE conference on Decision and Control, Tucson,1992:7-12
101.Polycarpou M M, Ioannou P A. Adaptive bounding techniques for stable neural control systems. In: Proceedings of the 34th Conference on Decision and Control, New Orleans, LA, 1995:2442-2447
102.Polycarpou M M. Stable adaptive neural control scheme for nonlinear systems. IEEE Transactions on Automatic Control, 1996,41(3):447-451
103.Sun F C, Sun Z Q, Woo P Y. Stable neural network-based adaptive control for sampled-data nonlinear systems. IEEE Transactions on Neural Networks, 1998, 9(5):956-968
104.Sun F C, Sun Z Q, Chen Y B et al. Neural adaptive tracking controller for robot manipulators with unknown dynamics. IEEE Proceedings, Control Theory and Applications, 2000, 147(3):366-370
105.Sun F C, Sun Z Q, Woo P Y. Neural network-based adaptive controller design of robotic manipulators with an observer. IEEE Transactions on Neural Networks, 2001,12(1):54-67
106.Sun F C, Li H X, Li L. Robot discrete adaptive control based on dynamics inversion using dynamical neural networks. Automatica, 2002, 38(11):1977-1983
107.Tzirkel-Hancock E, Fallside F. Stable control of nonlinear systems using neural networks. International Journal of Robust and Nonlinear Control, 1992(140)1:63-86
108.Chen S, Billings S A, Grant P M. Recursive hybrid algorithm for nonlinear system identification using radial basis function networks. International Journal of Control, 1992, 55(5):1050-1070
109.Karakasoglu A, Sundareshan M K. A recurrent s neural network-based adaptive variable structure model-following control of robotic manipulators. Automatica, 1995,31(10):1495-1507
110.Rovithakis G A, Chritodoulou M A. Adaptive neural control unknown plants using dynamical neural networks. IEEE Transactions on Systems,Man and Cybernetics,1994,24(3):400-412
111.Jagannathan S, Lewis F L. Multilayer discrete-time neural-net controller with guaranteed performance. IEEE Transactions on Neural Netwoks, 1996,7(1):107-130
112.Yesildirek A, Vandegrift M W, Lewis F L. Neural network controller for flexible-link robots. In: Proceedings of IEEE International Symposium on Intelligent Control. Columbus, Ohio, 1994:63-68
113.Jagannathan S, Lewis F L, Pastravanu O. Discrete-time model reference adaptive control of nonlinear dynamical systems using neural networks. International Journal of Control, 1996, 64(2):217-239
114.Agannathan S. Adaptive fuzzy logic control of feedback linearizable discrete-time nonlinear systems under persistence of excitation. Automatica, 1998, 34(1):1295-1310
115.Kuljaca O, Lewis F L. Fuzzy logic neural network adaptive critic controller design. In: Proceedings of the 41th IEEE Conference on Decision and Control, Las Vegas, 2004:3356-3361
116.Kim Y H, Lewis F L. Neural network output feedback control of robot manipulators. IEEE Transactions on Robotics and Automation, 1999,15(2):301-309
117.Narendra K S, Parthasarathy K. Identification and control of dynamical systems using neural network. IEEE Transactions on Neual Networks, 1990,1(1):4-27
118.Edgar N S, Miguel A B. Adaptive recurrent neural control for nonlinear system tracking. IEEE Transactions on Systems, Man, and Cybernetics, Part B:Cybernetics,2000,30(6):886-889
119.Huang J Q, Lewis F L. Neural-netwoks predictive control for nonlinear dynamic systems with time-delay. IEEE Transactions on Neural Networks, 2003,14(2):377-389
120.Markiewicz B. Analysis of the computed torque drive method and comparison with conventional position servo for a computed-controlled manipulator. Jet Propulsion Laboratory Technical Memo 33-601,March,1973
121.Paul R C. Modeling trajectory calculation and servoing of a computer controlled arm. A. I. Memo 177,Stanford Artificial Intellegence Laboratory,Stanford University,1972
122.Kreutz K. On manipulator control by exact linearization. IEEE Transaction on Automatic Control, 1989, 7(3):763-767
123.Wang L L, Tsai W H. Car safty driving aided by 3-D image analysis techniques. Proc. Microelectronics and Information Science and Technology Workshok, Hsinchu, Taiwan, R.O.C., 1986:687-701
124.机器人技术国家工程研究中心, 中科院沈阳自动化研究所. AGVS 产品及其应用. 机器人技术与应用. 1999(5):13-15
125.邬永革, 杨静宇. 多传感器数据融合的概念方法和实现. 机器人, 1995, 17(增刊):564-568
126.袁军, 黄心汉, 陈锦江. 基于多传感器的智能机器人信息融合、控制结构和应用. 机器人, 1994, 16(5): 313-320
127.Hackett J K, Shah M. Multi-sensor fusion: a perspective. Proc. Of IEEE Int. Conf. on Robotics and Automation, 1990:1324-1336
128.Houzelle S, Giraudon G. Contribution to multisensor fusion formalization. Robotics and Autonomous Systems, 1994, 13: 68-85
129.Giralt G. A multi-level planning and navigation system for a mobile: a first approach to HILARE. In: Proc. 6th Int. Joint Conf. on Artificial Intelligence. Tokyo, Japan, 1979:335-337
130.Miller W T, Aldrich C M. Rapid learning using CMAC neural networks: real time control of an unstable system. Proceedings of the International Conference on Artificial Neural Networks, 1991:1202-1207
131.Jeremy P G, Evangelos E M. Vision-based path following by using a neural network guidance system. Journal of Robotics System, 1994:11:57-66
132.Kleeman L. Optimal estimation of position and heading for mobile robots using ultrasonic beacons and dead reckoning. Robotica, 2003,11(2):97-103
133.董再励, 王光辉, 田彦涛等. 自主移动机器人激光全局定位系统研究. 机器人, 2000, 22(3):207-210
134.Rajagopalan R. Guidance control for automatic guided vehicle employing binary camera vision. Proc. of the IEEE Inter. Conf. on Robotics and Automation, 1991,l3:2496-2501
135.Y kanayama . A Locomotion Control Method for Autonomous Vehicles. Proc. of the IEEE Inter. Conf. on Robotics and Automation, 1988,l3:1315-1317
136.Nelson W L. A locomotion control method for autonomous vehicles. Proc. of IEEE Inter. Conf. on Robotics and Automation, 1988, 13:1315-1317
137.Lee S S, Williams J H. A fast tracking error control method for an autonomous. Mobile Robot. Robotica, 1993, 11: 209-215
138.Zhang Y J. Quantitative study of 3-D gradient operators. Image and Vision Computing, 1993, 11:611-622
139.章毓晋. 图象工程——图象处理与分析. 北京:清华大学出版社, 1999,182-185
140.朱仲涛, 张再兴. 边缘提取算子的微分不变性.计算机学报. 1999, 22( 9): 903-910
141.Spreeuwers L J. Neural network edge detector. Proc SPIE, 1991, 1451: 204-215
142.Dhawan A P, Dufrensne T. Low-level image processing and edge enhancement using a self-organizing neural network. Proc IEEE J Conf on Neural Networks, 1990: 503-510
143.Xue K, Breznik C W. A neural-net computing algorithm for detecting edges in a gray scale image. Proc. 29th EIII Conf on Decision and Control, 1990, 4: 2368-2373.
144.Chao C-H, Dhawan A P. Edge detection using a Hopfield neural network. Optical Engineering, 1994, 33:3739-3747
145.黎明, 严超华, 刘高航. 基于堆栈滤波器和 Hopfield 神经网络的边界检测法. 中国图象图形学报, 1999, 4A(7): 562-567
146.黎明, 严超华, 刘高航. 基于前向神经网络和 Hopfield 反馈神经网络的边界检测方法. 中国图象图形学报, 1999, 4A(8): 663-667
147.应骏, 叶秀清, 顾伟康. 一个基于知识的边沿提取算法. 中国图象图形学报, 1999,
4A(3):239-242.
148.李向吉, 丁润涛. 脉冲噪声污染图象中的数学形态边缘检测器. 中国图象图形学报, 1998,
3A(11): 903-906
149.陆军, 王润生. 一种基于尺度空间理论的直线抽取算法. 中国图象图形学报, 2000, 5A(8):693-698
150.吴卫国, 陈辉堂, 王月娟 等. 基于彩色图象的移动机器人定位. 机器人, 1999, 21(5):340-346
151.郑宏, 潘励.基于遗传算法的图象阈值的自动选取. 中国图象图形学报, 1999, 4A(4): 327-330.
152.高永英, 张利, 吴国威. 一种基于灰度期望值的图象二值化算法. 中国图象图形学报, 1999, 4A(6): 524-527
153.Aufrere R, Chapuis R, Chausse F. A Dynamic vision algorithm to locate a vehicle on a nonstructured road. The International Journal of Robotics Research. 2000, 19(5): 411-423
154.姚玉荣, 章毓晋. 利用小波和矩进行基于形状的图象检索. 中国图象图形学报, 2000, 5A(3): 206-210
155.齐丙辰, 大川善邦. 计算机视觉在球类机器人和行为理解研究中的应用与发展. 中国图象图形学报. 1998, 3(9):770-773
156.Kehtarnavaz N, Grisewold N C, Lee J S. Visual control of an autonomous vehicle(BART)-The vehicle following problem. Veh. Technol, 1991, 40(3):654-662,
157.Thorpe C, Hebert M H, Kanade T et al. Vision and navigation for the carnegie-mellon navlab. Pattern Analysis and Machine Intelligence, 1988, 10(3):362-373.
158.Schuster R, Ansari N, Hashemi A B. Steering a robot with vanishing points. Robotics and Automation, 1993, 9(4):491-498
159.Ishiguro H, Tsuji S. Applying panoramic sensing to autonomous map making by a mobilerobot. Proc. International Conference on Advanced Robotics, 1993:127-132
160.Madsen C B, Andersen C S. Optimal landmark selection for triangulation of robot position. Robotics and Autonomous Systems, 1998,29(1):277-292
161.Cao Z L, Oh S J, Hall E L. Ominidirectional dynamic vision positioning for a mobile robot. Journal of Robotic System, 1986, 3(1):5-17
162.Yagi Y, Kawato S, Tsuji S. Real-time ominidiretional image sensors(COPIS) for vision-guided navigation. IEEE Trans. On Robotics and Automation, 1994, 10(1):11-21
163.董再励, 郝颖明, 朱枫. 一种基于视觉的移动机器人定位系统. 中国图象图形学报, 2000, 5A(8):
688-692
164.王荣本, 徐友春, 李庆东等. AGVS 图象识别多分支路径的研究. 中国图象图形学报, 2000, 5A(8):632-637
165.清源计算机工作室. MATLAB 高级应用——图形及影象处理. 机械工业出版社, 2000, 273-318
166.John J. Craig 著,员超等译. 机械人学导论. 北京:机械工业出版社,2006.6
167.Jorge A. Fundamentals of robotic mechanical systems. New York: Spriger-Verlag, 2003,13-129
168.梅凤翔,刘端,罗勇.高等分析力学.北京:北京理工大学出版社,1991
169.Jiang Z. P. Lyapunov design of global state and output feedback trackers for nonholonomic control systerms. International Journal of Control, 2000,73(9): 744-761
170.张硕生,余达太.轮式移动机械手的优化构型.北京科技大学学报,2000,22(6):565-568
171.胡晓敏,张友军,朱淼良.移动机器人导航模型的设计方法.机器人, 1997,19(4):282-286
172.林怡青,周其节,毛宗源.一种移动机器人系统的运动学解法.华南理工大学学报(自然科学版),2000,28(4):66-70
173.达朝平,孙茂相,尹朝万.轮式移动机器人规划起点选择的新方法.机器人,1999,7(4):240-243
174.赵新华,曹作良.可移动机器人运动学模型与控制原理.机器人, 1994,16(4):215-218
175.周刚,陈辉堂,吴卫国.基于 DSP-TMS320C31 的轮式移动机器人控制系统设计.电子与自动化, 1999, 5:7-9
176.吕广明,孙立宁,唐余勇. 五自由度上肢康复机器人的运动学逆解. 黑龙江大学自然科学学报,2007,24(1):54-57
177.Paul R P. Robot manipulators, mathematics, programming and control. Cambridge,Mass: MIT Press, 1981
178.Seriji H. A unified approach to motion control of mobile manipulators. The International Journal of Robotics Research, 1998, 17(2):107
179.Yamamoto Y, Yun X. Coordination locomotion and manipulator of a mobile manipulator. IEEE Transaction on Automatic Control, 1994,39(6):1326
180.Carriker W F, Krogh P K. Path planning for mobile manipulators for multiple task execution. IEEE Transaction on Robotics and Automation, 1991,24(4):347
181.Yiu Y K. On the dynamics of parallel manipulators. In: Proceedings of the 2001 IEEE International Conference on Robotics & Automation, Seoul Korea, 2001, 21～28
182.Murry R M, Li Z, Sastry S S. A mathematical introduction to robotic manipulation. CRC,1994.
183.常宗瑜,杨咸启,谭俊哲. 指数积方法在空间机构运动分析中的应用.机械设计,2002,19(7):26-28
184.李佳宁,易建强,赵冬斌等. 一种全方位移动机械手的体系结构设计与分析. 机器人,2004,26(3):272-276
185.Schoner G, Dose M. Dynamics of behavior: theory and applications for autonomous robot architectures. Robotics and Autonomous System, 1995, 16: 213-245
186.林义忠. 自主轮式移动机器人信号检测与智能控制:[博士学位论文], 西安理工大学,2006
187.Abdessemed F, Monacelli E, Benmahammed K. A new approach for mobile manipulator motion control. IEEE Transaction on Automatic Control, 2001, 46:1203-1207
188.师名林,赵新华. 四自由度串联机械手的逆动力学建模及仿真. 天津理工大学学报,2006,22(5):37-40.
189.Kim Y H, Lewis F L. Neural network output feedback control of robot manipulators. IEEE Transactions on Robotics and Automation, 1999,15(2):301-309
190.Craig J. Adaptive cntrol of mchanical mnipulators. Reading,MA,Addison-Wesley,1988
191.Slotine J J E, Li W. On the adaptive control of robot manipulators. The International Journal of Robotics Research,1987,6(3):49-59
192.Slotine J J E, Li W. Adaptive manipulator control: a case study. IEEE Transactions on Automatic Control, 1988, 33(11):995-1003
193.Simon Haykin. Neural Network.北京:机械工业出版社, 2004:256-443
194.Elman J L. Finding structure in time. Cognitive Science,1990,14:179-211
195.Poznyak A S, Yu W, Sanchez E N et al. Nonlinear adaptive trajectory tracking using dynamical neural networks. IEEE Transactions on Neural Networks, 1999, 10(6):1402-1411
196.Puskorius G V, Feldamp L A, Davis J L I. Dynamic neural network methods applied to on-vehicle idle speed control. Proceedings of IEEE, 1996, 84:1407-1420
197.Kosmatopoulos E B, Polycarpou M M, Christodoulou M A et al. High-order neural network structures for identification of dynamical systems. IEEE Transactions on Neural Networks, 1995,6(2):422-43
198.Funahashi K. On the approximate realization of continuous mapping by neural networks. Neural Networks,1989,2:183-199
199.Hornik K, Stinchcomb M. Multilayer feedforward networks are universal approximators. Neural Netwoks,1989,2:359-366
200.Girosi F, Poggio T. Networks and the best approximation property. Biological Cybernetics, 1990, 63:169-176
201.Bass E. Robust control of nonlinear systems using normbounded neural networks. Proceedings of Computer Science, University of Massachusetts MA,1993,196-202
202.Hartman E, Keeler D. Predicting the future: advantages of semilocal units. Neural Computation, 1991, 3(4):566-578
203.Kohonen T. The self-organizing map. Proceedings of The IEEE,1990, (78)9:1464-1480
204.Kohonen T. The self-organizing Maps. Berlin Heidelberg:Springer-Verlag,1995
205.Ojala T, Vuorimaa P. Modified Kohonen’s learning laws for RBF network. Computerized Medical Imaging and Graphics, 2001,(25)1:47-59
206.Ku C C, Lee K Y. Diagonal recurrent neural networks for dynamical systems control. IEEE Transactions on Neual Networks,1995, (6)1:144-156
207.Draye J P S, Pavisic D A, Cheron G A et al. Dynamic recurrent neural networks: a dynamical analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,1996,(26)5:692-706
208.Jin L, Nikiforuk P N, Gupta M M. Adaptive control of discrete-time nonlinear systems using recurrent nrural networks. Control Theory and Applications,1994, (141)3:169-176
209.Sun F C,Sun Z Q, Li L et al. Nuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators. Fuzzy Sets and Systems,2003,(134)1:177-133
210.Rovithakis G A, Chritodoulou M A. Adaptive control with recurrent high-order neural networks — theory and industrial applications. Spinger-Verlag London Limited,2000
211.Ge S S, Lee T H, Harris C J. Adaptive neural network control of robotic manipulators. World Scientific Publishing Co. Pte. Ltd.,1998
212.Ge S S, Li G Y, Lee T H. Adaptive NN control for a class of strict feedback discrete-time nonlinear systems. Automatica,2003,39(3):807-819
213.Bloch A. M., Reyhanoglu M., McClamroch N H. Control and stabilization of non-holonomic Caplygin dynamic systems. International Journal of Robust and Nonlinear Control, 2001,11(3):191-214
214.Fierro R., Lewis F. L. Practical point stavilization of a non-holonomic mobile robots using neural networks. Proc 35th IEEE Conference of Decision and Control. Kobe, japan,1996:1722-1727
215.Wang S. Y., Huo W, Xu W L. Order reduced stabilization design of nonholonomic chained systems based on new canonical forms. Proc 38th IEEE Conf Decision Control, Phoenix, AZ, 1999:3464-3469
216.张明路,肖光辉等. 化学危险反应器泄漏检测与修补移动机械手系统. 技术报告,河北工业大学,2005.5
2. 张明路,关柏青,丁承君.基于彩色视觉和模糊控制的移动机器人的路径跟踪.中国机械工程,2004,13(8):636-639.
3. 李丽宏.基于双目显微立体视觉系统的研究.河北工业大学学报,2003,31(6):21-24.
4. 罗荣海.基于平行接近法的对运动目标跟踪的研究. 机器人技术与应用,2001(6):25-27.
5. Triend E, Kringman D J. Stereo vision and navigation within buildings. IEEE Int Conf. Robotics and Automation, 1987:1725-1730.
6. 王建刚, 董再励, 徐心平. 遥控作业移动机器人环境方法研究. 机器人, 1997, 19(4):244-249.
7. 马兆青, 袁增任. 基于栅格方法的移动机器人实时导航和避障. 机器人, 1996, 18(6):344-348.
8. 马保离, 霍伟. 移动机器人的路径跟踪与镇定. 机器人, 1995, 17(6):358-362.
9. 日本机器人学会. 机器人技术手册. 北京:科学出版社, 1996.
10. Madarasz R L, Heing L C, Crimp R F et al. The design of autonomous vehicle for the disabled. IEEE Joint Robotics and automation, RA2, 1986:117-126.
11. Tillema H G. An overview of the mobile autonomous robot Twente Project, MART-93, Tmwente University, WA315, 1993:315-319.
12. Egeland O, Berglund E, Sordalen O J. Exponential stabilization of a nonholonomic underwater vehicle with constant desired configuration. Proc. IEEE Inter. Conf. On Robotics and Automation, 1994:1234-1245.
13. Sheng L. Robust and intelligent control of mobile manipulators. [Dissertation]. Toronto: University of Toronto, 2001.
14. Saeed B. Niku, Introduction to Robotics: Analysis, Systems, Application. USA:Pearson Education, 2001:1-154
15. Fred G. Martin.Robotic Explorations A Hands-on Introduction to Engineering. USA:Pearson Education ,Inc.,2004:1-263
16. 卢韶芳,刘大维.自主式移动机器人导航研究现状及其相关技术.农业机械学报, 2002, 33(2):112-116
17. 欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究.机器人,2000, 22(6):521-526
18. Triendl E, Kriegman D. Stereo vision and navigation within building. IEEE Int.Conf.Robotics and Automation, Raleigh, NC. 1987:1725-1730
19. Dickmanns E D, Zapp A. Autonomous high speed road vehicle guidance by computer vision. IFAC 10th World Congress, Munich, FRG,1988:221-226
20. Turk M A. Video road-following for the autonomous land vehicle. IEEE Int.Conf.Robotics and Automation, Raleigh, NC. 1987:1542-1547
21. Netra J, Tardos T D, Horn J et al. Fusion rang and intensity images for mobile robot location. IEEE Transactions on Robotics and Automation, 1999, 15(1):76-84
22. Everett C H R. Survey of collision avoidance and ranging sensors for mobile robots. Robotics and Autonomous Systems, 1989, 5(1):65-68
23. Tanner H G., Kyriakopoulos K J, Krikelis N I. Advanced agricultural robots: kinematics and dynamics of multiple mobile manipulators handling non-rigid material. Computers andElectronics in Agriculture, 2001, 31(5): 91-105
24. 王栋耀, 马旭东, 戴先中. 基于声纳的移动机器人沿墙导航控制. 机器人, 2004,(4):179-184
25. 孟江华, 朱纪洪, 孙增圻. 未知环境下基于传感器的移动机器人路径规划新方法. 机器人, 2005,(4):86-91
26. 付宜利, 顾晓宇, 王树国. 基于模糊控制的自主机器人路径规划策略研究. 机器人, 2004,(6):54-59
27. 王敏, 金波, 黄心汉. 基于传感器和模糊规则的机器人在动态障碍环境中的智能运动控制. 控制理论与应用, 2000,(6):124-129
28. 徐国华, 谭民. 移动机器人的发展现状及其趋势. 机器人技术与应用, 2001,(3):115-120
29. 王越超. 我国危险作业机器人研究开发取得新进展. 机器人技术与应用,2005,(6):11-14
30. 蔡自兴. 智能控制及移动机器人研究进展. 中南大学学报(自然科学版), 2005,(5):108-113
31. 王仁奎, 李仲男, 赵耀明等. 反恐战士----广州卫富机器人. 机器人技术与应用, 2003,(3):61-64
32. 胡传平. 消防机器人的开发与应用. 机器人技术与应用, 2003, (5):147-152
33. 陈亮, 杨汝清, 谢霄鹏. 基于视觉的高压带电清扫机器人瓷瓶自动定位伺服系统. 机器人, 2004, (2):134-139
34. 肖永利, 张琛. 微型飞行器的研究现状与关键技术. 宇航学报, 2001(5):38-42
35. Saeed B N. Scheme for active positional correction of robot arms. Proceedings of the International Conference on CAD/CAM, Robotics, and Factories of the Future, Columbia,1991:590-596
36. Fred G. Martin.robotic explorations a hands-on introduction to engineering. USA:Pearson Education ,Inc.,2004:1-263
37. 卢韶芳,刘大维.自主式移动机器人导航研究现状及其相关技术.农业机械学报, 2002,
33(2):112-116
38. 欧青立,何克忠. 室外智能移动机器人的发展及其关键技术研究. 机器人, 2000, 22(6):521-526
39. Yamamoto Y, Yun X P. Coordinating locomotion and manipulation of a mobile manipulator. Proceedings of the 31st Conference on Decision and Control[C]. Tucson,1992:2643-2648
40. Seraji H. Motion Control of mobile manipulators.Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Piscataway, 1993:2056-2063
41. Carriker W F, Khosla P K, Krogh B H. Path planning for mobile manipulators for multiple task execution. IEEE Transactions on Robotics and Automation, 1991, 7(30):403-408
42. 张硕生,余达太.轮式移动机械手的点—点运动规划方法.北京科技大学学报,2001,23(1):81-84
43. 张硕生,余达太.轮式移动机械手的多点运动规划方法.北京科技大学学报,2001,23(2):177-180
44. Foulon G, Fourquet J Y, Renaud M. Planning point-to-point paths for nonhonolomic mobile manipulators. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Victoria, Canada, 1998:374-379
45. Tchon K, Jakubiak J, Muazynski R . Regular jacobian motion planning algorithms for mobile manipulators . IFAC[C].2002
46. Tanner H G, Kyriakopoulos K J. Nonholonomic motion planning for mobile manipulators. Proceedings of IEEE International Conference on Robotics and Automation[C]. San Francisco, 2000:1233-1238
47. Akira M, Seiji F, Yamamoto M. Trajectory planning of mobile manipulator with end – Effector’s specified path. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. Maui, Hawaii, 2001:2264-2269
48. Tan J D, Xi N. Unified model approach for planning and control of mobile manipulators.Proceedings of IEEE International Conference on Robotics and Automation[C]. Arlington, 2001:1-8
49. Huang Q, Tanie K, Sugano S. Coordinated motion planning for a mobile manipulator considering stability and manipulation. International Journal of Robotics Research, 2000,19(8):732-742
50. Yoshio Y, Yun X. Coordinating locomotion and manipulation of a mobile manipulator. IEEE Trasactions on Automatic Control, 1994, 39 (6): 1326-1332
51. Dubowsky S, Tanner A B. A study of the dynamics and control of mobile manipulators subjected to vehicle disturbances. In: Proceedings of 4th Int. Symp. of Robotics Research, Santa Cruz, CA. 1987: 111-117
52. Yamamoto Y, Yun X. A modular approach to dynamic modeling of a class of mobile manipulator. International Journal of Robotic and Automation, 1997, 12 (2): 41-48
53. Saha S K, Angeles J. Kinematics and dynamics of a three-wheeled 2-DOF AGV. Ieee Int. Conf. on Rob. & Autom., Piscataway, NJ, 1989, 3: 1572-1577
54. Qing Y, Chen I M. Variational-vector calculus formulation for dynamics of nonholonomic mobile manipulator system. IEEE International Conference on Robotics and Automation, Seoul,Korea, 2001: 216-226
55. 张硕生,余达太. 轮式移动操作机器人的动力学模型.北京石油化工学院学报,2002,10(2):22-27
56. 吴玉香,胡跃明. 轮式移动机械臂的建模与仿真研究. 计算机仿真,2006,23(1):147-151
57. Liu K, Lewis F L. Decentralized continuous robust controller for mobile robots. Proc. 1990 Int. Conf. obot. And Autom, Cincinnati, OH, May 1990:1822-1827
58. Yamamoto Y, Yun X. Control of mobile manipulators following a moving surface. In: International Conference of Robotics and Automation, Atlanta, GA, 1993, 3:1-6
59. Yamamoto Y, Yun X. Coordinating locomotion and manipulation of a mobile manipulator. Automation Control, 1996, 39(6): 1326-1332
60. Yamamoto Y, Yun X. Effect of the dynamic interaction on coordinated control of mobile manipulator. IEEE Transaction on Robotics and Automations, 1996, 12(5) :816-824
61. Wiens G J. Effects of dynamics coupling in mobile system. Proceedings of World Conference on Robotic Systems[C].1989:43-57
62. Wiens G J, Jang W M. Passive joint control of dynamic coupling in mobile robots. International Journal of Robotic Research, 1994,13(3):209-220.
63. Yamamoto Y, Yun X P. Control of mobile manipulators following a moving surface. Proceedings of IEEE International Conference on Robotics and Automation[C]. Piscataway, 1993:1-6
64. Lee H K, Takubo T, Arai H, et al. Control of mobile manipulators for power assist systems. Journal of Robotics Systems, 2000,17(9):469-477
65. Jagannathan S, Zhu S Q. Path planning and control of a mobile base with nonholonomic constraints. Robotica, 1994(12):529-540
66. Evangelos P, John P. Planning and model-based control for mobile manipulators. International Journal of Environment and Pollution, 2007(30)2:213-230
67. Liu K, Lewis F L. Decentralized continuous robust controller for mobile robots. Journal of Applied Mechanics, Transactions ASME, 2005(72)2: 306-308
68. Sheng L, Goldenberg A A. Robust damping control of mobile manipulators. IEEE Transactions on Systems, Man and Cybernetics, Part B, 2002, 32(1):126-132.
69. Sheng L, Goldenberg A A. Neural-network control of mobile manipulators. IEEE Transactions on Neural Networks, 2001, 12(5):1121-1133.
70. Chung J H, Velinsky Steven A, Hess R A. Interaction control of a redundant mobile manipulator. International Journal of Robotics Research, 1998, 17(12):1302-1309
71. Yamamoto Y, Yun X P. Coordinated obstacle of a mobile manipulator. Proceedings of IEEE International Conference on Robotics and Automation[C].1995:2255-2260
72. Ogren P, Egerstedt M, Hu X. Reactive mobile manipulation using dynamic trajectory Tracking. Proceedings of IEEE International Conference on Robotics and Automation[C]. San Francisco, 2000:3473-3478.
73. FU L P. An adaptive routing algorithm for in vehicle route guidance systems with real time information[J]. Transportation Research B, 2001, 35(8): 749-765
74. Dong WJ,Chou JM, Feng GL, Progress in the study of retrospective numerical scheme and the climate prediction, Acta Mechanica Sinica,2004,20(5):38-41
75. 董文杰,徐文立. 移动机械手的跟踪控制. 控制与决策,2001,16(6):914-917.
76. 董文杰,徐文立. 移动机械手的鲁棒控制. 控制理论与应用,2002,19(3):345-348
77. 董文杰,徐文立. 不确定非完整移动机械手的鲁棒控制. 清华大学学报,2002,42(9):1261-1264.
78. Jagannathan S. Discrete-time fuzzy logic control of a mobile robot with an onboard manipulators. International Journal of Systems Science, 1997, 28(12):1195-1209.
79. Kang S, Komoriya K, Yokoi K, et al. Reduced inertial effect in damping-based posture control of mobile manipulator. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 2001:488-493
80. Yamamoto Y, Yun X P. Effect of the dynamic interaction on coordinated control of mobile manipulators. IEEE Transactions on Robotics and Automation, 1996, 12(5):816-824
81. Ghasempoor S. A measure of stability for mobile manipulator. Proceedings of IEEE International Conference on Robotics and Automation[C]. 1995:2249-2254.
82. Rey D A, Papadopoulos E G. On-line automatic tipover for a mobile manipulator. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1997:1273-1278.
83. Yoneda. K. Tumble stability criterion of integrated locomotion and manipulation. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1996:870-876
84. Dubowsky S. Planning mobile manipulator motions considering vehicle dynamic stability constrains[A]. Proceedings of IEEE International Conference on Robotics and Automation[C]. 1989:1271-1276.
85. Sugano S. Stability control for mobile manipulator using potential method. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C].1994:839-846
86. Huang Q, Sugano S, Tanie K. Stability compensation of a mobile manipulator by manipulator motion: feasibility and planning. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems[C]. 1997:1285-1292
87. 马明山,朱绍文,何克忠.室外机器人定位技术研究. 电工技术学报,1998,13(2):43-46
88. 陈延国,于澎,高振东.自主移动机器人定位方法的研究现状. 应用科技, 2002,29(11):41-43
89. Rumelhart G A. Stable adaptive neuron-control design via Lyapunov function derivation estmation. Automatica, 2001,37(8):1213-1221
90. Lewis F L, Liu K, Yesildirek A. Neural net robot controller with guaranteed tracking performance. IEEE Transactions on Neural Networks, 1995,6(3):703-715
91. Lewis F L, Yesildirek A, Liu K. Multilayer neural net robot controller: structure and stability proofs. IEEE Transactions on Neural Networks, 1996,7(2):388-399
92. Chen F C, Khalil H K. Adaptive control of nonlinear continuous-time systems using neural networks. International Journal of Control, 1992, 55(6):1299-1317
93. Chen F C, Liu C C. Adaptively controlling nonlinear continuous-time systems using multilayer neural networks. IEEE Transactions on Automatic Control, 1994,39(6):1306-1310
94. Chen F C, Khalil H K. Adaptive control of a class of nonlinear discrete time systems using neural networks. IEEE Transactions on Automatic Control, 1995,40(5):791-801
95. Sanner R M, Slotine J J E. Stable adaptive control and recursive identification using radial gaussian networks. In: Proceedings of IEEE Conference on Decision and Control, Brighton, 1991:2116-2123
96. Sanner R M, Slotine J J E. Gaussian networks for direct adaptive control. IEEE Transactions on Neural Networks, 1992, 3(5):837-863
97. Sanner R M, Slotine J J E. Stable adaptive control of robot manipulators using neural networks. Neural Computation, 1995, 7(3):753-790
98. Sanner R M, Slotine J J E. Structurally dynamic wavelet networks for the adaptive control of uncertain robotic systems. In: Proceedings of the 34th IEEE Conference on Decision and Control, New Orleans, LA,1995:2460-2467
99. Polycarpou M M, Ioannou P S. Identification and control of nonlinear systems using neural network models: design and stability analysis. EE-Report 91-09-01, University of Southern California,1991
100.Polycarpou M M, Ioannou P A. Neural networks as on-line approximators of nonlinear systems. In: Proceedings of IEEE conference on Decision and Control, Tucson,1992:7-12
101.Polycarpou M M, Ioannou P A. Adaptive bounding techniques for stable neural control systems. In: Proceedings of the 34th Conference on Decision and Control, New Orleans, LA, 1995:2442-2447
102.Polycarpou M M. Stable adaptive neural control scheme for nonlinear systems. IEEE Transactions on Automatic Control, 1996,41(3):447-451
103.Sun F C, Sun Z Q, Woo P Y. Stable neural network-based adaptive control for sampled-data nonlinear systems. IEEE Transactions on Neural Networks, 1998, 9(5):956-968
104.Sun F C, Sun Z Q, Chen Y B et al. Neural adaptive tracking controller for robot manipulators with unknown dynamics. IEEE Proceedings, Control Theory and Applications, 2000, 147(3):366-370
105.Sun F C, Sun Z Q, Woo P Y. Neural network-based adaptive controller design of robotic manipulators with an observer. IEEE Transactions on Neural Networks, 2001,12(1):54-67
106.Sun F C, Li H X, Li L. Robot discrete adaptive control based on dynamics inversion using dynamical neural networks. Automatica, 2002, 38(11):1977-1983
107.Tzirkel-Hancock E, Fallside F. Stable control of nonlinear systems using neural networks. International Journal of Robust and Nonlinear Control, 1992(140)1:63-86
108.Chen S, Billings S A, Grant P M. Recursive hybrid algorithm for nonlinear system identification using radial basis function networks. International Journal of Control, 1992, 55(5):1050-1070
109.Karakasoglu A, Sundareshan M K. A recurrent s neural network-based adaptive variable structure model-following control of robotic manipulators. Automatica, 1995,31(10):1495-1507
110.Rovithakis G A, Chritodoulou M A. Adaptive neural control unknown plants using dynamical neural networks. IEEE Transactions on Systems,Man and Cybernetics,1994,24(3):400-412
111.Jagannathan S, Lewis F L. Multilayer discrete-time neural-net controller with guaranteed performance. IEEE Transactions on Neural Netwoks, 1996,7(1):107-130
112.Yesildirek A, Vandegrift M W, Lewis F L. Neural network controller for flexible-link robots. In: Proceedings of IEEE International Symposium on Intelligent Control. Columbus, Ohio, 1994:63-68
113.Jagannathan S, Lewis F L, Pastravanu O. Discrete-time model reference adaptive control of nonlinear dynamical systems using neural networks. International Journal of Control, 1996, 64(2):217-239
114.Agannathan S. Adaptive fuzzy logic control of feedback linearizable discrete-time nonlinear systems under persistence of excitation. Automatica, 1998, 34(1):1295-1310
115.Kuljaca O, Lewis F L. Fuzzy logic neural network adaptive critic controller design. In: Proceedings of the 41th IEEE Conference on Decision and Control, Las Vegas, 2004:3356-3361
116.Kim Y H, Lewis F L. Neural network output feedback control of robot manipulators. IEEE Transactions on Robotics and Automation, 1999,15(2):301-309
117.Narendra K S, Parthasarathy K. Identification and control of dynamical systems using neural network. IEEE Transactions on Neual Networks, 1990,1(1):4-27
118.Edgar N S, Miguel A B. Adaptive recurrent neural control for nonlinear system tracking. IEEE Transactions on Systems, Man, and Cybernetics, Part B:Cybernetics,2000,30(6):886-889
119.Huang J Q, Lewis F L. Neural-netwoks predictive control for nonlinear dynamic systems with time-delay. IEEE Transactions on Neural Networks, 2003,14(2):377-389
120.Markiewicz B. Analysis of the computed torque drive method and comparison with conventional position servo for a computed-controlled manipulator. Jet Propulsion Laboratory Technical Memo 33-601,March,1973
121.Paul R C. Modeling trajectory calculation and servoing of a computer controlled arm. A. I. Memo 177,Stanford Artificial Intellegence Laboratory,Stanford University,1972
122.Kreutz K. On manipulator control by exact linearization. IEEE Transaction on Automatic Control, 1989, 7(3):763-767
123.Wang L L, Tsai W H. Car safty driving aided by 3-D image analysis techniques. Proc. Microelectronics and Information Science and Technology Workshok, Hsinchu, Taiwan, R.O.C., 1986:687-701
124.机器人技术国家工程研究中心, 中科院沈阳自动化研究所. AGVS 产品及其应用. 机器人技术与应用. 1999(5):13-15
125.邬永革, 杨静宇. 多传感器数据融合的概念方法和实现. 机器人, 1995, 17(增刊):564-568
126.袁军, 黄心汉, 陈锦江. 基于多传感器的智能机器人信息融合、控制结构和应用. 机器人, 1994, 16(5): 313-320
127.Hackett J K, Shah M. Multi-sensor fusion: a perspective. Proc. Of IEEE Int. Conf. on Robotics and Automation, 1990:1324-1336
128.Houzelle S, Giraudon G. Contribution to multisensor fusion formalization. Robotics and Autonomous Systems, 1994, 13: 68-85
129.Giralt G. A multi-level planning and navigation system for a mobile: a first approach to HILARE. In: Proc. 6th Int. Joint Conf. on Artificial Intelligence. Tokyo, Japan, 1979:335-337
130.Miller W T, Aldrich C M. Rapid learning using CMAC neural networks: real time control of an unstable system. Proceedings of the International Conference on Artificial Neural Networks, 1991:1202-1207
131.Jeremy P G, Evangelos E M. Vision-based path following by using a neural network guidance system. Journal of Robotics System, 1994:11:57-66
132.Kleeman L. Optimal estimation of position and heading for mobile robots using ultrasonic beacons and dead reckoning. Robotica, 2003,11(2):97-103
133.董再励, 王光辉, 田彦涛等. 自主移动机器人激光全局定位系统研究. 机器人, 2000, 22(3):207-210
134.Rajagopalan R. Guidance control for automatic guided vehicle employing binary camera vision. Proc. of the IEEE Inter. Conf. on Robotics and Automation, 1991,l3:2496-2501
135.Y kanayama . A Locomotion Control Method for Autonomous Vehicles. Proc. of the IEEE Inter. Conf. on Robotics and Automation, 1988,l3:1315-1317
136.Nelson W L. A locomotion control method for autonomous vehicles. Proc. of IEEE Inter. Conf. on Robotics and Automation, 1988, 13:1315-1317
137.Lee S S, Williams J H. A fast tracking error control method for an autonomous. Mobile Robot. Robotica, 1993, 11: 209-215
138.Zhang Y J. Quantitative study of 3-D gradient operators. Image and Vision Computing, 1993, 11:611-622
139.章毓晋. 图象工程——图象处理与分析. 北京:清华大学出版社, 1999,182-185
140.朱仲涛, 张再兴. 边缘提取算子的微分不变性.计算机学报. 1999, 22( 9): 903-910
141.Spreeuwers L J. Neural network edge detector. Proc SPIE, 1991, 1451: 204-215
142.Dhawan A P, Dufrensne T. Low-level image processing and edge enhancement using a self-organizing neural network. Proc IEEE J Conf on Neural Networks, 1990: 503-510
143.Xue K, Breznik C W. A neural-net computing algorithm for detecting edges in a gray scale image. Proc. 29th EIII Conf on Decision and Control, 1990, 4: 2368-2373.
144.Chao C-H, Dhawan A P. Edge detection using a Hopfield neural network. Optical Engineering, 1994, 33:3739-3747
145.黎明, 严超华, 刘高航. 基于堆栈滤波器和 Hopfield 神经网络的边界检测法. 中国图象图形学报, 1999, 4A(7): 562-567
146.黎明, 严超华, 刘高航. 基于前向神经网络和 Hopfield 反馈神经网络的边界检测方法. 中国图象图形学报, 1999, 4A(8): 663-667
147.应骏, 叶秀清, 顾伟康. 一个基于知识的边沿提取算法. 中国图象图形学报, 1999,
4A(3):239-242.
148.李向吉, 丁润涛. 脉冲噪声污染图象中的数学形态边缘检测器. 中国图象图形学报, 1998,
3A(11): 903-906
149.陆军, 王润生. 一种基于尺度空间理论的直线抽取算法. 中国图象图形学报, 2000, 5A(8):693-698
150.吴卫国, 陈辉堂, 王月娟 等. 基于彩色图象的移动机器人定位. 机器人, 1999, 21(5):340-346
151.郑宏, 潘励.基于遗传算法的图象阈值的自动选取. 中国图象图形学报, 1999, 4A(4): 327-330.
152.高永英, 张利, 吴国威. 一种基于灰度期望值的图象二值化算法. 中国图象图形学报, 1999, 4A(6): 524-527
153.Aufrere R, Chapuis R, Chausse F. A Dynamic vision algorithm to locate a vehicle on a nonstructured road. The International Journal of Robotics Research. 2000, 19(5): 411-423
154.姚玉荣, 章毓晋. 利用小波和矩进行基于形状的图象检索. 中国图象图形学报, 2000, 5A(3): 206-210
155.齐丙辰, 大川善邦. 计算机视觉在球类机器人和行为理解研究中的应用与发展. 中国图象图形学报. 1998, 3(9):770-773
156.Kehtarnavaz N, Grisewold N C, Lee J S. Visual control of an autonomous vehicle(BART)-The vehicle following problem. Veh. Technol, 1991, 40(3):654-662,
157.Thorpe C, Hebert M H, Kanade T et al. Vision and navigation for the carnegie-mellon navlab. Pattern Analysis and Machine Intelligence, 1988, 10(3):362-373.
158.Schuster R, Ansari N, Hashemi A B. Steering a robot with vanishing points. Robotics and Automation, 1993, 9(4):491-498
159.Ishiguro H, Tsuji S. Applying panoramic sensing to autonomous map making by a mobilerobot. Proc. International Conference on Advanced Robotics, 1993:127-132
160.Madsen C B, Andersen C S. Optimal landmark selection for triangulation of robot position. Robotics and Autonomous Systems, 1998,29(1):277-292
161.Cao Z L, Oh S J, Hall E L. Ominidirectional dynamic vision positioning for a mobile robot. Journal of Robotic System, 1986, 3(1):5-17
162.Yagi Y, Kawato S, Tsuji S. Real-time ominidiretional image sensors(COPIS) for vision-guided navigation. IEEE Trans. On Robotics and Automation, 1994, 10(1):11-21
163.董再励, 郝颖明, 朱枫. 一种基于视觉的移动机器人定位系统. 中国图象图形学报, 2000, 5A(8):
688-692
164.王荣本, 徐友春, 李庆东等. AGVS 图象识别多分支路径的研究. 中国图象图形学报, 2000, 5A(8):632-637
165.清源计算机工作室. MATLAB 高级应用——图形及影象处理. 机械工业出版社, 2000, 273-318
166.John J. Craig 著,员超等译. 机械人学导论. 北京:机械工业出版社,2006.6
167.Jorge A. Fundamentals of robotic mechanical systems. New York: Spriger-Verlag, 2003,13-129
168.梅凤翔,刘端,罗勇.高等分析力学.北京:北京理工大学出版社,1991
169.Jiang Z. P. Lyapunov design of global state and output feedback trackers for nonholonomic control systerms. International Journal of Control, 2000,73(9): 744-761
170.张硕生,余达太.轮式移动机械手的优化构型.北京科技大学学报,2000,22(6):565-568
171.胡晓敏,张友军,朱淼良.移动机器人导航模型的设计方法.机器人, 1997,19(4):282-286
172.林怡青,周其节,毛宗源.一种移动机器人系统的运动学解法.华南理工大学学报(自然科学版),2000,28(4):66-70
173.达朝平,孙茂相,尹朝万.轮式移动机器人规划起点选择的新方法.机器人,1999,7(4):240-243
174.赵新华,曹作良.可移动机器人运动学模型与控制原理.机器人, 1994,16(4):215-218
175.周刚,陈辉堂,吴卫国.基于 DSP-TMS320C31 的轮式移动机器人控制系统设计.电子与自动化, 1999, 5:7-9
176.吕广明,孙立宁,唐余勇. 五自由度上肢康复机器人的运动学逆解. 黑龙江大学自然科学学报,2007,24(1):54-57
177.Paul R P. Robot manipulators, mathematics, programming and control. Cambridge,Mass: MIT Press, 1981
178.Seriji H. A unified approach to motion control of mobile manipulators. The International Journal of Robotics Research, 1998, 17(2):107
179.Yamamoto Y, Yun X. Coordination locomotion and manipulator of a mobile manipulator. IEEE Transaction on Automatic Control, 1994,39(6):1326
180.Carriker W F, Krogh P K. Path planning for mobile manipulators for multiple task execution. IEEE Transaction on Robotics and Automation, 1991,24(4):347
181.Yiu Y K. On the dynamics of parallel manipulators. In: Proceedings of the 2001 IEEE International Conference on Robotics & Automation, Seoul Korea, 2001, 21～28
182.Murry R M, Li Z, Sastry S S. A mathematical introduction to robotic manipulation. CRC,1994.
183.常宗瑜,杨咸启,谭俊哲. 指数积方法在空间机构运动分析中的应用.机械设计,2002,19(7):26-28
184.李佳宁,易建强,赵冬斌等. 一种全方位移动机械手的体系结构设计与分析. 机器人,2004,26(3):272-276
185.Schoner G, Dose M. Dynamics of behavior: theory and applications for autonomous robot architectures. Robotics and Autonomous System, 1995, 16: 213-245
186.林义忠. 自主轮式移动机器人信号检测与智能控制:[博士学位论文], 西安理工大学,2006
187.Abdessemed F, Monacelli E, Benmahammed K. A new approach for mobile manipulator motion control. IEEE Transaction on Automatic Control, 2001, 46:1203-1207
188.师名林,赵新华. 四自由度串联机械手的逆动力学建模及仿真. 天津理工大学学报,2006,22(5):37-40.
189.Kim Y H, Lewis F L. Neural network output feedback control of robot manipulators. IEEE Transactions on Robotics and Automation, 1999,15(2):301-309
190.Craig J. Adaptive cntrol of mchanical mnipulators. Reading,MA,Addison-Wesley,1988
191.Slotine J J E, Li W. On the adaptive control of robot manipulators. The International Journal of Robotics Research,1987,6(3):49-59
192.Slotine J J E, Li W. Adaptive manipulator control: a case study. IEEE Transactions on Automatic Control, 1988, 33(11):995-1003
193.Simon Haykin. Neural Network.北京:机械工业出版社, 2004:256-443
194.Elman J L. Finding structure in time. Cognitive Science,1990,14:179-211
195.Poznyak A S, Yu W, Sanchez E N et al. Nonlinear adaptive trajectory tracking using dynamical neural networks. IEEE Transactions on Neural Networks, 1999, 10(6):1402-1411
196.Puskorius G V, Feldamp L A, Davis J L I. Dynamic neural network methods applied to on-vehicle idle speed control. Proceedings of IEEE, 1996, 84:1407-1420
197.Kosmatopoulos E B, Polycarpou M M, Christodoulou M A et al. High-order neural network structures for identification of dynamical systems. IEEE Transactions on Neural Networks, 1995,6(2):422-43
198.Funahashi K. On the approximate realization of continuous mapping by neural networks. Neural Networks,1989,2:183-199
199.Hornik K, Stinchcomb M. Multilayer feedforward networks are universal approximators. Neural Netwoks,1989,2:359-366
200.Girosi F, Poggio T. Networks and the best approximation property. Biological Cybernetics, 1990, 63:169-176
201.Bass E. Robust control of nonlinear systems using normbounded neural networks. Proceedings of Computer Science, University of Massachusetts MA,1993,196-202
202.Hartman E, Keeler D. Predicting the future: advantages of semilocal units. Neural Computation, 1991, 3(4):566-578
203.Kohonen T. The self-organizing map. Proceedings of The IEEE,1990, (78)9:1464-1480
204.Kohonen T. The self-organizing Maps. Berlin Heidelberg:Springer-Verlag,1995
205.Ojala T, Vuorimaa P. Modified Kohonen’s learning laws for RBF network. Computerized Medical Imaging and Graphics, 2001,(25)1:47-59
206.Ku C C, Lee K Y. Diagonal recurrent neural networks for dynamical systems control. IEEE Transactions on Neual Networks,1995, (6)1:144-156
207.Draye J P S, Pavisic D A, Cheron G A et al. Dynamic recurrent neural networks: a dynamical analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,1996,(26)5:692-706
208.Jin L, Nikiforuk P N, Gupta M M. Adaptive control of discrete-time nonlinear systems using recurrent nrural networks. Control Theory and Applications,1994, (141)3:169-176
209.Sun F C,Sun Z Q, Li L et al. Nuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators. Fuzzy Sets and Systems,2003,(134)1:177-133
210.Rovithakis G A, Chritodoulou M A. Adaptive control with recurrent high-order neural networks — theory and industrial applications. Spinger-Verlag London Limited,2000
211.Ge S S, Lee T H, Harris C J. Adaptive neural network control of robotic manipulators. World Scientific Publishing Co. Pte. Ltd.,1998
212.Ge S S, Li G Y, Lee T H. Adaptive NN control for a class of strict feedback discrete-time nonlinear systems. Automatica,2003,39(3):807-819
213.Bloch A. M., Reyhanoglu M., McClamroch N H. Control and stabilization of non-holonomic Caplygin dynamic systems. International Journal of Robust and Nonlinear Control, 2001,11(3):191-214
214.Fierro R., Lewis F. L. Practical point stavilization of a non-holonomic mobile robots using neural networks. Proc 35th IEEE Conference of Decision and Control. Kobe, japan,1996:1722-1727
215.Wang S. Y., Huo W, Xu W L. Order reduced stabilization design of nonholonomic chained systems based on new canonical forms. Proc 38th IEEE Conf Decision Control, Phoenix, AZ, 1999:3464-3469
216.张明路,肖光辉等. 化学危险反应器泄漏检测与修补移动机械手系统. 技术报告,河北工业大学,2005.5