A robust hand-eye calibration method based on schur matrix decomposition

Abstract

Accuracy, efficiency and stability are important criteria of hand-eye calibration method. We proposed a novel hand-eye calibration method. As traditional two-step hand-eye calibration methods, first, we solve rotation parameters and then translation vector can be deserved immediately. We obtain a general solution from one observation and decrease degree of freedom from 3 to 2. Through this way, we can use more constraint equations to improve hand-eye calibration's accuracy within same time. Observational data preprocessing is one of the basic problems unresolved of hand-eye calibration algorithms. We derived judge-equation based on schur matric decomposition in order to delete wild data. The method is validated by both simulations and experiments. The results show that the proposed method performs better than the other four popular hand-eye calibration methods.