Vision-based Virtual Fixtures Generation for Robotic-Assisted Polyp Dissection Procedures

Abstract

Polyp dissection requires very accurate detection of the region of interest and high-precision cutting with adequate safety margins. Robot-assisted polyp dissection is a solution to accomplish high-quality intervention. This paper proposes a method to constrain the robot to follow an accurate dissection path based on Virtual Fixtures (VF). The VFs are created via specific control points obtained directly from images of the surgical scene and are updated by the vision algorithm. The VF constraints can autonomously adapt themselves to environment changing during the surgical intervention. The entire pipeline is validated through experiments on the da Vinci Research Kit (dVRK) robot.