Point-based registration using Extended Kalman Filter in medical robotic system

The goal of this paper is to develop a needle insertion robotic system for ultrasound-guided minimally invasive surgery, which is composed of a robot, a surgical planning subsystem and a pose tracking device. In the surgery procedure, the target coordinate should be transformed from one coordinate frame to another coordinate frame through point-based registration. The point-based registration using Extended Kalman Filter is proposed and the state estimation is given by the transformation matrix solved by the traditional Singular Value Decomposition method. In this case, the Extended Kalman Filter can quickly converge and avoid trapped in local minima of the function. Then, the simulation experiment is carried out to evaluate the proposed method accuracy and system accuracy. The results demonstrate that the proposed methods improve the coordinate transformation accuracy and the efficiency of the medical robotic system.