Advanced robotic assistance in microsurgery, such as automation, requires an accurate estimation of the state of the robotic forceps. In this paper, we propose a robust and accurate forceps tracking method to estimate the full state of the forceps (i.e., the position, posture, and grip parameters) using visual information obtained from stereo microscopic images and kinematic information obtained from the robotic sensory information, forward kinematics, and hand-eye coordination. An online method for updating the hand-eye coordination was also developed using an extended Kalman filter to cancel the hand-eye coordination errors caused by the repositioning of the microscope. The experimental results showed that the proposed method could accurately and robustly estimate the state of the robotic forceps even after the repositioning of the microscope.

Forceps tracking is an important element of high-level surgical assistance such as visual servoing and surgical motion analysis. In many computer vision algorithms, artificial markers are used to enable robust tracking; however, markerless tracking methods are more appropriate in surgical applications due to their sterilizability. This paper describes a robust, efficient tracking algorithm capable of estimating the full state parameters of a robotic surgical instrument on the basis of projective contour modeling using a 3-D CAD model of the forceps. Thus, the proposed method does not require any artificial markers. The likelihood of the contour model was measured using edge distance transformation to evaluate the similarity of the projected CAD model to the microscopic image, followed by particle filtering to estimate the full state of the forceps. Experimental results in simulated surgical environments indicate that the proposed method is robust and time-efficient, and fulfills real-time processing requirements.

The master and slave surgical assistant systems have been studied actively. However, regarding the master system, the manipulator should be designed for each surgical field because the target workspace and precision are different. Furthermore, operability is important for safety reasons. Therefore, the authors analyzed the motion of surgeon first and then developed a master manipulator suitable for the operation of micro neuro surgery. Some experiments were conducted to evaluate the control method and show the effectiveness of the proposed manipulator control method.