Kinematics Redundancy Identification of Arbitrary Serial Robot

Redundant parameters in robot kinematic error model may affect the accuracy and robustness of identification results, and should be removed before calibration. In this paper, the pose error model of end-effector was derived, and redundant parameters of robot with arbitrary structure were obtained by analyzing the linear correlation columns of Jacobian matrix. To verify the correctness of the proposed method, a self-calibration method based on plane constraint was proposed. The simulation results show that non-redundant parameter identification model can improve the position accuracy regardless of the presence of noise, while the full-parameter identification model is susceptible to noise and the identification results do not converge. The correctness of the parameter redundancy analysis is proved by the experiments on Franka Emika serial robot. After removing redundant parameters, the position errors reduced from 2.41mm to 1.20mm.