Efficient multi-parameter calibration method for CVC assist robot with servo-navigation system

High precision and servo-puncture navigation system is of great significance for the clinical application of central venous catheter (CVC) puncture-assist robot guided by ultrasound. Therefore, the authors proposed a new servo-predictive navigation system, which can track the posture of robot and predict the puncturing needle path in real time, effectively solving the limitation of conventional path plan line, such as path plan line deviation. For ensuring the accuracy of this predictive navigation system, a multi-parameter calibration method using particle swarm optimisation (PSO) based on self-adaptive system was adopted in this research, and applied to authors' self-developed servo-predictive navigation system for puncture-assist robot MRAPS II. Experimental results indicated that by calibrating mechanical and control parameters, the authors can effectively improve the accuracy of servo-navigation system. It greatly promoted the use of CVC puncture-assist robot in clinical application.