A framework for preoperative planning of robotics-assisted minimally invasive cardiac surgery (ramics) under geometric uncertainty

Hamidreza Azimian, Rajni V. Patel, Michael D. Naish, Bob Kiaii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Robotics and Automation, ICRA 2011
Pages5018-5023
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Robotics and Automation, ICRA 2011 - Shanghai, China
Duration: May 9 2011May 13 2011

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2011 IEEE International Conference on Robotics and Automation, ICRA 2011
CountryChina
CityShanghai
Period5/9/115/13/11

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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