Abstract: In both Eye-in-Hand and Eye-to-Hand robotic visual controls, problems such as limited field of view or tracking target loss remain. Thus, online measurement cannot be performed within a certain distance and a certain degree, and a closed-loop control cannot be constructed. Based on Eye-in-Hand visual control and the theoretical shortest measuring distance L_min, a visual servo combining the closed-loop and open-loop controls was proposed. When above L_min, an iterative compensation method was proposed to adjust the attitude with the online measured data. In contrast, when below L_min, a feed-forward compensation for relative linear motion was integrated to improve the positioning accuracy, estimating the error by the data determined by actually moving the path of the robot record by the visual system. As shown by several experiments, this method can effectively enhance the position accuracy.