Safety-Enhanced Model-Free Visual Servoing for Continuum Tubular Robots Through Singularity Avoidance in Confined Environments

Abstract

Minimally invasive procedures have gained ever-increasing popularity due to their advantages of smaller incisions, faster recoveries, fewer complications, and reduced scarring to name a few. With the force exertion and curvilinear flexibility at their distal end effectors, the continuum tubular robots have the potential to perform robot-assisted trans-orifice minimally invasive surgery, such as transnasal and transoral operations. During these procedures, it is important and challenging for the continuum tubular robot to automatically adjust its pose according to the target surgical sites and compensate for undesired disturbance, such as respiratory motions. In this paper, a singularity-avoidance visual servoing algorithm based on Jacobian Optimization has been proposed to improve safety and control continuum tubular robots based on intra-operative visual feedback in confined environments. Without the prior knowledge of robot kinematics or hand-eye calibration between the robot and the endoscope, the proposed model-free eye-in-hand visual servoing technique is capable of accomplishing the targeting tasks by adopting the safety-enhanced singularity avoidance mechanism and an efficient image-processing algorithm. The multiple experiments, including simulations, experiments conducted in a confined environment, and cadaveric studies, have been implemented and demonstrated to illustrate the superiority of the proposed singularity-avoidance visual servoing method. © 2019 IEEE.