Adaptive Backstepping and MEMS Force Sensor for an MRI-Guided Microrobot in the Vasculature

Laurent Arcèse (1) , Matthieu Fruchard (1) , Felix Beyeler (2) , Antoine Ferreira (1) , B.-J. Nelson (3)

1 IRAUS - Département Images, Robotique, Automatique et Signal [Orléans]
2 FemtoTools GmbH
3 IRIS - Institute of Robotics and Intelligent Systems

A microrobot consisting of a polymer binded aggregate of ferromagnetic particles is controlled using a Magnetic Resonance Imaging (MRI) device in order to achieve targeted therapy. The primary contribution of this paper is the design of an adaptive backstepping controller coupled with a high gain observer based on a nonlinear model of a microrobot in a blood vessel. This work is motivated by the difficulty in accurately determining many biological parameters, which can result in parametric uncertainties to which model-based approaches are highly sensitive. We show that the most sensitive parameter, magnetization of the microrobot, can be measured using a Micro-Electro-Mechanical Systems (MEMS) force sensor, while the second one, the dielectric constant of blood, can be estimated on line. The efficacy of this approach is illustrated by simulation results.

Domaines: Automatique / Robotique

Laurent Arcèse, Matthieu Fruchard, Felix Beyeler, Antoine Ferreira, B.-J. Nelson. Adaptive Backstepping and MEMS Force Sensor for an MRI-Guided Microrobot in the Vasculature. 2011 IEEE International Conference on Robotics and Automatics, May 2011, Shangaï, China. pp 4121-4126. ⟨hal-00656004⟩