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Diffusion-based motion planning for a nonholonomic flexible needle model

  • Wooram Park
  • , Jin Seob Kim
  • , Yu Zhou
  • , Noah J. Cowan
  • , Allison M. Okamura
  • , Gregory S. Chirikjian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

181 Scopus citations

Abstract

Fine needles facilitate diagnosis and therapy because they enable minimally invasive surgical interventions. This paper formulates the problem of steering a very flexible needle through firm tissue as a nonholonomic kinematics problem, and demonstrates how planning can be accomplished using diffusion-based motion planning on the Euclidean group, SE(3). In the present formulation, the tissue is treated as isotropic and no obstacles are present. The bevel tip of the needle is treated as a nonholonomic constraint that can be viewed as a 3D extension of the standard kinematic cart or unicycle. A deterministic model is used as the starting point, and reachability criteria are established. A stochastic differential equation and its corresponding Fokker-Planck equation are derived. The Euler-Maruyama method is used to generate the ensemble of reachable states of the needle tip. Inverse kinematics methods developed previously for hyperredundant and binary manipulators that use this probability density information are applied to generate needle tip paths that reach the desired targets.

Original languageEnglish
Title of host publicationProceedings of the 2005 IEEE International Conference on Robotics and Automation
Pages4600-4605
Number of pages6
DOIs
StatePublished - 2005
Event2005 IEEE International Conference on Robotics and Automation - Barcelona, Spain
Duration: Apr 18 2005Apr 22 2005

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2005

Conference

Conference2005 IEEE International Conference on Robotics and Automation
Country/TerritorySpain
CityBarcelona
Period04/18/0504/22/05

Keywords

  • Euler-Maruyama method
  • Medical robotics
  • Needle steering
  • Nonholonomic path planning
  • Probability density function

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