Increasing Accuracy in Image-Guided Robotic Surgery Through Tip Tracking and Model-Based Flexion Correction

Abstract

Robot assistance can enhance minimally invasive image-guided surgery, but flexion of the thin surgical instrument shaft impairs accurate control by creating errors in the kinematic model. Two controller enhancements that can mitigate these errors are improved kinematic models that account for flexing and direct measurement of the instrument tip's position. This paper presents an experiment quantifying the benefits of these enhancements in an effort to inform development of an image-guided robot control system accurate in the presence of quasi-static instrument flexion. The study measured a controller's ability to guide a flexing instrument along user-commanded motions while preventing incursions into a forbidden region virtual fixture. Compared with the controller using neither enhancement, improved kinematics and reduced maximum incursion depth into the forbidden region by 28%, tip tracking by 67%, and both enhancements together by 83%.