Dual-Tool Distance Constraint for Robot Length Parameter Identification in Confined Calibration Space

Abstract

In robotic automation, compact layouts and the limited range of measurement devices often confine the robot’s calibration space, leading to ill-conditioned Jacobian matrices for length parameters and significant estimation errors. To address this issue, joint configurations in the confined calibration space are modeled as perturbations around those under a fixed end-effector position. By applying matrix perturbation theory, the relationship between the smallest singular value of the identification matrix and the joint configuration perturbations is established. Building on this theoretical basis, a novel dual-tool distance constraint method is introduced to alleviate the ill-conditioning of the identification matrix and enhance parameter identification accuracy. The proposed method was validated using an ABB IRB 4600 industrial robot. Experimental results in the confined calibration space demonstrate that, compared with conventional methods, the proposed approach not only mitigates ill-conditioning but also significantly improves the robot’s positioning accuracy.