Robot Hand-Eye Calibration Using Structure-from-Motion

In this paper, we propose a new flexible method for hand-eye calibration. The vast majority of existing hand-eye calibration techniques require a calibration rig that is used in conjunction with camera pose estimation methods. Instead, we combine structure-from-motion with known robot motions, and we show that the solution can be obtained in linear form. The latter solves for both the hand-eye parameters and the unknown scale factor inherent with structure-from-motion methods. The algebraic analysis that is made possible with such a linear formulation allows investigation of not only the well-known case of general screw motions but also of such singular motions as pure translations, pure rotations, and planar motions. In essence, the robot-mounted camera looks to an unknown rigid layout, tracks points over an image sequence, and estimates the camera-to-robot relationship. Such a self-calibration process is relevant for unmanned vehicles, robots working in remote places, and so forth. We conduct a large number of experiments that validate the quality of the method by comparing it with existing ones.