A Simultaneous Optimization Method of Calibration and Measurement for a Typical Hand–Eye Positioning System

Abstract

Hand-eye calibration is one of the key technologies of robot hand and eye coordination operation. The calibration accuracy directly affects the measurement accuracy of hand-eye system. Due to the influence of environmental noise and disturbance, the results of hand-eye calibration usually contain errors. The hand-eye parameters with errors are used for vision measurement, which will lead to the calibration error into the measurement results. This error transfer phenomenon will inevitably affect the accuracy of visual measurement. In this article, a simultaneous optimization method of calibration and measurement is proposed. Based on the analysis of the motion characteristics, the measurement and calibration model with nonlinear constraints is established. An iterative method is proposed along with the closed-form solution to improve the calibration accuracy. Furthermore, the advantages of the proposed method over traditional methods are discussed. Simulation and experiment are carried out to analyze the calibration and measurement accuracy, error propagation, and solution conditions. The results demonstrate that the proposed method realizes the simultaneous optimization of calibration and measurement and can effectively suppress the influence of calibration error on measurement accuracy.