Optimal motion control for image-based visual servoing by decoupling translation and rotation

Image-based visual servoing interprets image change directly to camera motion, and control the position and pose of a robot mounting a camera to reach the goal, where the camera obtains just the same image as a given goal image. 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 estimated beforehand, and sometimes it results in largely inefficient motion. This paper points out that this inefficient motion is caused by interferences of translation and rotation of images. Then, we propose two algorithms 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 straightforwardly