A Framework for Preoperative Planning of Robotics-Assisted Minimally Invasive Cardiac Surgery (RAMICS) Under Geometric Uncertainty

摘要

In this paper, robust preoperative planning of RAMICS is formulated. The intent of the proposed planning framework is to improve surgical outcomes by contemplating the intraoperative conditions of the surgical procedure and the geometry of the patient's thoracic anatomy. This includes improvements in target reachability, instrument dexterity for critical surgical tasks, surgical task feasibility and visibility. Given the patient's preoperative computed tomography images of the chest, the planning framework aims to determine the optimal location of the access ports on the ribcage, along with the optimal pose of the robotic arms relative to the patient's anatomy. To minimize susceptibility of the results to intraop-erative geometric uncertainty, the planning is formulated as a Generalized Semi-Infinite Program (GSIP) with a convex lower level problem and a multi-criteria objective function. By solving the GSIP, tolerable geometric uncertainty within the task space is increased by eliminating the likelihood of collisions and joint limit violation in a neighborhood of the surgical target.