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

Abstract

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%.

Effect of Combined Motion on Force Transmission of a Flexible Instrument

“…Moreover, the reduction in friction force also leads to improved motion transmission [6]. A better estimation of instrument tip motion also helps in accurate control of thin flexible surgical instrument [7].…”

Modified PD based bilateral nonlinear teleoperation with flexible link robots

“…For instance, one of the earliest studies in this field substituted Flexible Link Slave robots by robots with joint flexibility [1]. In the other study, flexibility in link has been modelled as a quasi-static behavior to minimize modelling error, disregarding flexion dynamics of the elastic manipulator [2]. Besides, stability and transparency of these systems are not taken into account in some publications [3].…”

An evaluation of closed-loop control options for continuum manipulators

“…As a result, reduced positioning accuracy and dexterity, as compared to traditional rigid robotic systems, is common. To improve system performance while enabling more autonomous capabilities, a number of researchers have focused on the use of in-vivo feedback control [1,3,5,6,7,8,9,10]. In-vivo feedback is the use of position, orientation, shape or other data collected while the manipulator is at work inside the patient collected via radiographic, electromagnetic and other Manuscript [7,11,12,13,14,15].…”