Kinematics parameter identification and accuracy evaluation method for neurosurgical robot

Abstract

The kinematic model parameter deviation is the main factor affecting the positioning accuracy of neurosurgical robots. To obtain more realistic kinematic model parameters, this paper proposes an automatic parameters identification and accuracy evaluation method. First, an identification equation contains all robot kinematics parameter was established. Second, a multiple-pivot strategy was proposed to find the relationship between end-effector and tracking marker. Then, the relative distance error and the inverse kinematic coincidence error were designed to evaluate the identification accuracy. Finally, an automatic robot parameter identification and accuracy evaluation system were developed. We tested our method on both laboratory prototypes and real neurosurgical robots. The results show that this method can realize the neurosurgical robot kinematics model parameters identification and evaluation stably and quickly. Using the identified parameters to control the robot can reduce the robot relative distance error by 33.96% and the inverse kinematics consistency error by 67.30%.