This paper proposes a review of the robot’s vision control scheme using the data moving method, to improve the accuracy and processing speed for the tracking of a moving target. The vision system model, which can actively adjust the camera parameters for the camera and robot position changes is used for this study. The method of processing the vision data obtained during robot movement toward the target can be classified into a batch method using all the acquired data, and a data moving method using only limited data. In an effort to reduce the number of vision data obtained while the robot moves toward the target, the proposed control scheme estimates the optimal number of robot moving points near the target, to exclude the old data and use only the limited data obtained near the target recently. In this study, limited data are utilized. In order to show the effectiveness of the proposed control scheme, we set the control method based on the batch processing method, and then compared these two results with the accuracy and the processing time by performing the experiments of the slender-bar moving target tracking method.

This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera’s focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.