With the increasing popularity of industrial automation, manufacturers will inevitably make efforts to produce high value-added products in order to respond to market competition. Therefore, the tracking accuracy of robot manipulator featuring high configurability and flexibility, plays an essential role. Although the conventional robot manipulator has good repeatability, the kinematic accuracy often suffers from the error of mechanism. Aside from the kinematic accuracy, dynamic accuracy-- the ability to track a dynamic trajectory, is directly related to the workpiece quality and throughput. Good dynamic accuracy enables high product quality under high speed and complex scenario. In this paper, a dual loop iterative learning control algorithm is used to optimize the kinematic accuracy, and the dynamic accuracy of the robot manipulator with the maximum absolute error less than 0.2 mm. The controlled robot manipulator can be applied to high precision manufacturing processes.