Hand-eye calibration method with a three-dimensional-vision sensor considering the rotation parameters of the robot pose. (8th December 2020)

• Record Type: Journal Article
• Authors: Fu, Jinsheng; Ding, Yabin; Huang, Tian; Liu, Xianping
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 6(2020:Nov./Dec.)
• Publication Date: 2020-12-08
• Subjects: Machine vision -- hand-eye calibration -- 3D-vision sensor -- machining robot; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420977296
• Languages: English
• ISSNs: 1729-8806

Abstract

Hand-eye calibration is a fundamental step for a robot equipped with vision systems. However, this problem usually interacts with robot calibration because robot geometric parameters are not very precise. In this article, a new calibration method considering the rotation parameters of the robot pose is proposed. First, a constraint least square model is established assuming that each spherical center measurement of standard ball is equal in the robot base frame, which provides an initial solution. To further improve the solution accuracy, a nonlinear calibration model in the sensor frame is established. Since it can reduce one error accumulation process, a more accurate reference point can be used for optimization. Then, the rotation parameters of the robot pose whose slight errors cause large disturbance to the solution are selected by analyzing the coefficient matrices of the error items. Finally, the hand-eye transformation parameters are refined together with the rotation parameters in the nonlinear optimization solution. Some comparative simulations are performed between the modified least square method, constrained least square method, and the proposed method. The experiments are conducted on a 5-axis hybrid robot named TriMule to demonstrate the superior accuracy of the proposed method.