Three-Dimensional Controlled Motion of a Microrobot using Magnetic Gradients

Abstract

This paper presents an endovascular navigation of a ferromagnetic microdevice using MRI-based predictive control. The concept was studied for future development of microrobot designed to perform minimally invasive interventions in remote sites accessible through the human cardiovascular system. A system software architecture is presented illustrating the different software modules to allow 3D navigation of a microdevice in blood vessels, namely: (i) vessel path extraction, (ii) magnetic gradient steering, (iii) tracking and (iv) closed-loop navigation control. First, the navigation path of the microrobot into the blood vessel is extracted using Fast Marching Method from the pre-operation images (3D MRI imaging) to guide the microrobot from the injection point to the tumor area through the anarchic vessel network. Based on the pre-computed path, a Model Predictive Controller is proposed for robust time-multiplexed navigation along a 3D path in presence of pulsative flow.The simulation results suggest the validation of the proposed image processing and control algorithms.

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

“…In previous works [16,22] , we have proposed a framework enabling finding a minimal centered navigation path built upon the fast marching method (FMM), first introduced by Sethian [23] . In the FMM framework, the path finding problem is solved through the computation of the minimal action map U: C → ℝ þ , associated to an initial point x 0 on a domain C ⊂ ℝ d (with d ¼ 2 or 3).…”

“…A control module ( ) generates the magnetic gradient field to propel the microcarrier. Different control schemes have been sucessfully tested, such as a proportional-integral-derivative (PID) controller [15] , predictive controller [16] , or adaptive backstepping controller [17] . Moreover, the overall concept of the MRI-tracking system is based on the fact that both tracking and propulsion are possible with the manufacturer-supplied gradient coils of the MRI system.…”

Control of a magnetic microrobot navigating in microfluidic arterial bifurcations through pulsatile and viscous flow

“…In this paper we aim to embed the system model (4) in a predictive controller to follow efficiently a pre-planed path P extracted with the method proposed in [13]. …”

“…First, the centerline reference path P is computed automatically using the algorithm developed in [13]. Then, the pulsatile blood pump is started to fill out the pipes and the vascular phantom with different mixture of water/glycerol solutions.…”

“…Different viscosity environments are tested (ranging from 100% water-to-100% glycerol) under a systolic pulsatile flow. We demonstrate experimentally that the generalized predictive controller (GPC), developed previously in [13], is sufficiently robust against nonlinear model uncertainties (e.g. drag force and viscosity), external perturbations (systolic pulsatile flow) and noisy trajectory tracking measurements.…”