ABSTRACT
Robotic puncture system has been widely used in modern minimally invasive surgery, which usually uses hand-eye calibration to calculate the spatial relationship between the robot and the optical tracking system. However, the hand-eye calibration process is time-consuming and sensitive to environmental changes, which makes it difficult to guarantee the puncture accuracy of the robot. This study proposes an uncalibrated positioning method for puncture robot based on optical navigation. The method divides the target path positioning into two stages, angle positioning and position positioning, and designs angle image features and position image features respectively. The corresponding image Jacobian matrix is constructed based on the image features and updated by online estimation with a cubature Kalman filter to drive the robot to perform target path localization. The target path positioning results show that the method is more accurate than the traditional hand-eye calibration method and saves significant preoperative preparation time by eliminating the need for calibration.