S. L. Charreyron, Q. Boehler, B. Kim, C. Weibel, C. Chautems, B. J. Nelson
IEEE Transactions on Robotics, IEEE, vol. 37, no. 4, 2021, pp. 1009-1021
Abstract
Remote magnetic navigation is used for the manipulation of untethered micro and nanorobots, as well as tethered magnetic surgical tools for minimally invasive medicine. Mathematical modeling of the magnetic fields generated by magnetic navigation systems is a fundamental task in the control of such tools for biomedical applications. In this article, we describe and compare several existing and newly developed methods for representations of continuous magnetic fields using interpolation in the context of remote magnetic navigation. Clinical-scale electromagnetic navigation systems feature nonlinear magnetization and magnetization interactions between electromagnets, which renders accurate magnetic field modeling challenging. We first introduce a method that can adapt existing linear models to correct for nonlinear magnetization, with similar performance to the current state-of-the-art nonlinear model. Furthermore, we present a method based on convolutional neural networks.
