Workspace Measurement and Calibration of a Parallel RCM Craniotomy Surgery Robot

Abstract

This paper aims to improve the accuracy of a three degree-of-freedom surgery robot by means of calibration. The robot consists of a parallel Remote Center of Motion (RCM) mechanism which is designed for craniotomy surgery. The calibration method is based on the forward kinematic approach, which uses a nonlinear optimization model. The Levenberg-Marquaridt method is used as the optimization technique and the loss function is defined by the least square definition. Sixty experimental data are used for the optimization process, the data are obtained using a Leica total station camera to measure the end-effector position, another sixty measurement data are also obtained to use in the evaluation process. Seven kinematic parameters are considered for the optimization process. After the optimization process the loss function reduced to 0.0002453 square millimeters.