A noise-tolerant algorithm for robotic hand-eye calibration with or without sensor orientation measurement

An iterative algorithm for calibration of a robotic hand-eye relationship is presented. The hand-eye calibration can be performed by solving a system of homogeneous transformation equations of the form A _iX=XB_i, where X is the unknown sensor position relative to the robot wrist, A_i is the ith robot motion, and B_i is the ith sensor motion. Unlike existing approaches, the algorithm presented solves the kinematic parameters of X in one stage, thus eliminating error propagation and improving noise sensitivity. Furthermore, with the iterative algorithm, the parameters of X can be computed even when the rotational part of B_i is unknown. This is important since position is easier to measure than orientation. Comparative simulation studies show that the performance of the iterative algorithm is usually better than that of noniterative two-stage algorithms, regardless of whether the orientation part of B _i is used or not. This paper also discusses the application of the proposed method to calibration of a tool mounted on a robot manipulator