The training system of vascular interventional surgical robot based on Chai3D

Abstract

To overcome the disadvantages of traditional vascular interventional procedure, the vascular interventional surgical robot which is based on the master-slave control mode enters the clinical, and helps doctors to complete surgery. Because doctors do not touch the catheter directly while controlling the master-slave robot, which may damage the blood vessels and make patients at risk. In response to these problems, self-developed vascular interventional surgical robot is used as the application platform in this paper, and an approach based on Chai3D is developed to set up a virtual reality training system. This approach mainly achieves the flexible body modelling of catheter and the collision force feedback algorithm. Its establishment process contains four steps which are the establishment of a virtual space and the modelling of virtual objects, collision detection between virtual objects, collision force feedback and the display and update of images. The experiment shows that the flexible body modelling of this approach makes a good response of the deformations of catheter inside the blood vessel, and the results of collision force feedback algorithm match well with the data collected by sensors, and the matching rate is about 90%.