Preoperative Planning of Robotics-Assisted Minimally Invasive Cardiac Surgery Under Uncertainty

TL;DRAbstract

In this thesis, a computational framework for patient-specific preoperative planning of Robotics-Assisted Minimally Invasive Cardiac Surgery (RAMICS) is developed. It is expected that preoperative planning of RAMICS will improve the rate of success by considering robot kinematics, patient-specific thoracic anatomy, and procedure-specific intraoperative conditions. Given the significant anatomical features localized in the preoperative computed tomography images of a patient's thorax, port locations and robot orientations (with respect to the patient's body coordinate frame) are determined to optimize characteristics such as dexterity, reachability, tool approach angles and maneuverability. In this thesis, two approaches for preoperative planning of RAMICS are proposed that enable contemplation of uncertainties in preoperative data and surgical tasks. In the first approach, the problem is formulated as a Generalized Semi-Infinite Program (GSIP) with a convex lower-level problem to maxim

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