Design of collision detection algorithms and force feedback for a virtual reality training intervention operation system

Minimally invasive surgery (MIS) is a specialized surgical technique, the minimally invasive surgery compared to traditional surgery, not only can reduce the patient's pain, more can make the patients recover more quickly. But because the minimally invasive surgery is very complex, so the doctors need a lot of training to guarantee the realization of the surgery. In previous studies, we have developed a virtual reality training system. Based on CT image reconstruction of 3-d vessel model, we designed a 3 d model of the catheter. In order to provide the surgeon to meet the need of training sense of touch, we studied the force feedback and the collision detection algorithm. We design a system that contains three kinds of force: force feedback viscous force, friction force and impact force. Catheter force and viscous force between blood; Friction between the catheters means the power of the body and blood vessels; Catheter tip is the collision force between force and vessel. Then we develop a fast collision detection algorithm based on AABB bounding box (Axis Aligned) method. In this way, we can reduce the collision detection time, training in real time. Finally, we designed a few columns based on Phantom a control experiment. We also the contact force between the catheter and the blood vessels do the detailed analysis, combined with local collision detection algorithm to calculate the contact force and feedback to the operator through the Phantom handles.