Research Of The Minimally Invasive Neurosurgery Robot's Vision Navigation System

Robot vision is a practical technique formed with the development of robot technology and machine vision technique. At present, many robot aided cure systems have been applied to clinic medicine, which achieves great success. But the application of robot with vision to neurosurgery remains a popular research field.The aided operation of neurosurgery robot operative system is to transfer technical parameters to robot after operation program is made, then transform planned parameters to robot coordinates by means of mapping measurement and mapping algorithm of marks on the skull of patients, thus robot can automatically control the operative process according to intended operation program.The accuracy of stereo vision orientation plays a significant role in neurosurgery. Non-contact and high accuracy of vision orientation system ensures safety of neurosurgery and accuracy in the implementation of operation program. Robot vision orientation technology is emphasized by the advantages in terms of automatic, rapid, safe, high in accuracy and other performance, which will eventually take place of traditional frame orientation in neurosurgery.This paper based on the project of minimally invasive neurosurgery robot's vision navigation system. A subsystem is designed for this system according to the requirement of minimally invasive neurosurgery robot's vision navigation system. This paper has referred to many related data from both home and abroad, based on basic principle of stereo vision orientation and the current development status of neurosurgery robot.In this paper, the first chapter introduces the research significance and development status quo of the minimally invasive neurosurgery robot's vision navigation system. Rresearch contents are also included. The second chapter analyses the principle of stereo vision orientation and related key techniques and designs the program of stereo vision orientation based on actual conditions of the research. The third chapter emphasizes on the orientation model of camera calibration, hand-eye calibration and stereo vision in this vision system. The forth chapter introduces key techniques of image process software in this vision system. The fifth chapter demonstrates the experiment results on calibration and orientation of the vision orientation system and the analytical results. The last chapter presents a summary of the whole contexts and proposes some parts requiring improvement.