Abstract
Image-based visual servoing interprets image change directly to camera motion, and control the position and pose of a robot mounting a camera. It does not need 3D object models and is robust for image reading errors and noise. However, because its strategy is to simply minimize the differences between the goal image and the currently obtained image, trajectory of the robot motion cannot be expected beforehand, and sometimes it results in largely inefficient motion. This paper points out that this inefficient motion is caused by interferences of translating motion and rotation of images. Then, we propose two algorithm to decouple them by using the Homography and the epipolar condition held between the goal image and the current image, and to generate the optimal trajectory of the robot motion to reach the goal position straightforwardly.
