| Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment |
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| 作者姓名： | CUI Genqun LI Chunshu ZHANG Minglu School of Mechanical Engineering Hebei University of Technology Tianjin China |
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| 作者单位： | CUI Genqun LI Chunshu ZHANG Minglu School of Mechanical Engineering，Hebei University of Technology，Tianjin 300062，China |
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| 摘 要： | This paper studies the kinematic modeling of a mobile manipulator that consists of 5-DOF manipulator and an autonomous wheeled mobile platform.Then an artificial neural network to realize the coordination motion between manipulator and mobile platform is developed.On the basis of the task specifications,the algorithm determines the appropriate control variables to respond to the well tracking trajectory.The control strategy employed for either subsystem is achieved by using a robust supervised controller.A learning paradigm is used to produce the required reference variables for an overall cooperative behavior of the sys- tem.Simulation results are presented to show the effectiveness of this approach.
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Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment |
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| CUI Genqun LI Chunshu ZHANG Minglu School of Mechanical Engineering,Hebei University of Technology,Tianjin ,China.Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment[J].Journal of Wuhan University of Technology,2006(Z3). |
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| Authors: | CUI Genqun LI Chunshu ZHANG Minglu School of Mechanical Engineering Hebei University of Technology Tianjin China |
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| Affiliation: | CUI Genqun LI Chunshu ZHANG Minglu School of Mechanical Engineering,Hebei University of Technology,Tianjin 300062,China |
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| Abstract: | This paper studies the kinematic modeling of a mobile manipulator that consists of 5-DOF manipulator and an autonomous wheeled mobile platform.Then an artificial neural network to realize the coordination motion between manipulator and mobile platform is developed.On the basis of the task specifications,the algorithm determines the appropriate control variables to respond to the well tracking trajectory.The control strategy employed for either subsystem is achieved by using a robust supervised controller.A learning paradigm is used to produce the required reference variables for an overall cooperative behavior of the sys- tem.Simulation results are presented to show the effectiveness of this approach. |
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| Keywords: | mobile manipulator kinematics analysis nonholonomic constraints cooperative behavior artificial neural network |
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