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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 system. Simulation results are presented to show the effectiveness of this approach.