Informations

Type
article
Key
2017_tro_folio
Authors
Folio, David and Ferreira, Antoine
http://doi.org/10.1109/TRO.2016.2638446
01446482
2017_tro_folio.

Abstract

This paper introduces a two-dimensional autonomous navigation strategy of a 750 \mum steel microrobot along complex fluidic vascular network inside the bore of a clinical 3.0 T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation (MRN) of a microrobot along consecutive channels, the design of autonoumous navigation strategy is needed taking into account the major MRI technological constraints and physiological perturbations, e.g. non-negligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, susceptibility artifacts uncertainties, and so on. An optimal navigation planning framework based on Pareto optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750 \mum magnetic microrobots is rendered possible in a complex two-dimensional centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 mm/s with average tracking errors below 800 \mum with limited magnetic gradients \pm15 mT/m compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade

Keyword

  • microrobotics
  • magnetic resonance imaging
  • magnetic resonance navigation
  • multi-ojective planning.

BibTeX:

 @article{2017_tro_folio,
  title = {2D Robust Magnetic Resonance Navigation of a Ferromagnetic Microrobot using Pareto Optimality},
  author = {Folio, David and Ferreira, Antoine},
  journal = {IEEE Transactions on Robotics},
  year = {2017},
  number = {3},
  pages = {583--593},
  volume = {33},
  doi = {10.1109/TRO.2016.2638446},
  hal = {01446482},
  ieeexplore = {7829399},
  issn = {1552-3098},
  keywords = {Microrobotics, Magnetic Resonance Imaging,
  Magnetic Resonance Navigation, Multi-Ojective Planning.},
  publisher = {IEEE}
}