High Precision Calibration for Three-Dimensional Vision-Guided Robot System

Abstract

Calibration is an important premise for vision-guided robot system, especially for precise industrial operations on curved surfaces. Most of existing methods focus on one or partial union of errors including assembly error of the robot, relative pose error between the vision unit and the robot, or installation error of end effector, which is still challenging in practice. To solve this problem, this article proposes a new calibration method based on error correction matrix by which different manifestations of each error is unified. As the nonlinear equations formed by these matrices cannot be solved analytically, a numerical optimization solution based on Lie algebra is presented. Specifically, the matrices acquisition is formulated as the problem of minimizing the sum of distance deviations between actual and ideal tool center points. This problem is then solved by differentiating these matrices with a form of left multiplicative perturbation. In this way, a high precision joint calibration with multisource errors is achieved. The proposed method is verified by simulations and experiments.