A constrained optimization approach to virtual fixtures

Ming Li, Ankur Kapoor, Russell H. Taylor

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

Abstract

We describe a new method to generate virtual fixtures for surgical robot control which provide sophisticated ways to assist the surgeon. Different spatial motion constraints for human machine collaborative systems can be implemented by using this method if we know the required geometric constraints and the instantaneous kinematics of the robot. It is independent of manipulator types: teleoperative or cooperative controlled; admittance or impedance type. Our method uses weighted, linearized, multi-objective optimization framework to formalize a library of virtual fixtures for task primitives. We set the cost function based on the user's inputs, and set linearized subject function based on a combination of five basic geometric constraints. In this paper, we also illustrate the implementation for two sample tasks, which are useful for surgical applications, and provide the experimental results for these tasks.

Original languageEnglish (US)
Title of host publication2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
PublisherIEEE Computer Society
Pages1408-1413
Number of pages6
ISBN (Print)0780389123, 9780780389120
DOIs
StatePublished - 2005

Publication series

Name2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

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