Samuel Charreyron


Last Name

Charreyron

First Name

Samuel

ORCID

0000-0003-4636-3096

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2015 - 2019112020 - 20236
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Publications 1 - 10 of 17
  • Multiwavelength Light-Responsive Au/B-TiO2 Janus Micromotors
    Item type: Journal Article
    Jang, Bumjin; Hong, Ayoung; Kang, Ha Eun; et al. (2017)
    ACS Nano
  • Rodbot: A Rolling Microrobot for Micromanipulation
    Item type: Conference Paper
    Pieters, Roel S.; Tung, Hsi-Wen; Charreyron, Samuel; et al. (2015)
    Proceedings of 2015 IEEE International Conference on Robotics and Automation (ICRA)
  • Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks
    Item type: Conference Paper
    Yu, Ruoxi; Charreyron, Samuel; Boehler, Quentin; et al. (2020)
    2020 IEEE International Conference on Robotics and Automation (ICRA)
    Electromagnetic Navigation Systems (eMNS) can be used to control a variety of multiscale devices within the human body for remote surgery. Accurate modeling of the magnetic fields generated by the electromagnets of an eMNS is crucial for the precise control of these devices. Existing methods assume a linear behavior of these systems, leading to significant modeling errors within nonlinear regions exhibited at higher magnetic fields, preventing these systems from operating at full capacity. In this paper, we use a random forest (RF) and an artificial neural network (ANN) to model the nonlinear behavior of the magnetic fields generated by an eMNS. Both machine learning methods outperformed the state-of-the-art linear multipole electromagnet model (MPEM). The RF and the ANN model reduced the root mean squared error (RMSE) of the MPEM when predicting the field magnitude by approximately 40% and 87%, respectively, over the entire current range of the eMNS. At high current regions, especially between 30 and 35 A, the field-magnitude RMSE improvement of the ANN model over the MPEM was 37 mT, equivalent to 90% error reduction. This study demonstrates the feasibility of using machine learning to model an eMNS for medical applications, and its ability to account for complex nonlinear behavior at high currents. The use of machine learning thus shows promise in developing accurate field predicting models, and ultimately improving surgical procedures that use magnetic navigation. © 2020 IEEE.
  • Magnetic field interpolation for remote magnetic navigation in minimally invasive surgery
    Item type: Book Chapter
    Charreyron, Samuel; Nelson, Bradley (2022)
    Woodhead Publishing Series in Electronic and Optical Materials ~ Magnetic Materials and Technologies for Medical Applications
    Interpolation of magnetic field data can be used to model the fields generated by magnetic navigation system (MNS) for applications in medical robotics. Prediction of magnetic fields is required for the control of magnetically navigated tools at arbitrary positions in the workspace of an MNS. In this chapter, various interpolation methods are detailed and compared. The methods are divided into structured grid interpolation ones that perform interpolation on data located on regular grids using polynomial interpolation, and unstructured radial basis function-based ones, for which the data can be placed at arbitrary positions. This chapter also compares methods that are physically consistent ones, in that they attempt to obey physical constraints that are inherent to the magnetic fields, to methods that are unconstrained. Methods are compared based on their ability to predict magnetic field vectors and magnetic field gradient matrices at unmeasured locations using several numerical metrics, on a synthetic dataset representing fields generated by an MNS.
  • Navigation of a Rolling Microrobot in Cluttered Environments for Automated Crystal Harvesting
    Item type: Conference Paper
    Charreyron, Samuel; Pieters, Roel S.; Tung, Hsi-Wen; et al. (2015)
    Proceedings of 2015 IEEE International Conference of Intelligent Robots and Systems (IROS)
  • Real-Time Holographic Tracking and Control of Microrobots
    Item type: Journal Article
    Hong, Ayoung; Zeydan, Burak; Charreyron, Samuel; et al. (2017)
    IEEE Robotics and Automation Letters
  • Shared control of a magnetic microcatheter for vitreoretinal targeted drug delivery
    Item type: Conference Paper
    Charreyron, Samuel; Zeydan, Burak; Nelson, Bradley J. (2017)
    2017 IEEE International Conference on Robotics and Automation (ICRA)
  • Modeling Electromagnetic Navigation Systems
    Item type: Journal Article
    Charreyron, Samuel; Boehler, Quentin; Kim, Byungsoo; et al. (2021)
    IEEE Transactions on Robotics
    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.
  • Visual-Kinematic Monocular SLAM using a Magnetic Endoscope
    Item type: Other Conference Item
    Charreyron, Samuel; Boehler, Quentin; Millane, Alexander J.; et al. (2018)
    Proceedings, Hamlyn Symposium on Medical Robotics 2018
  • Magnetically powered microrobots: a medical revolution underway?
    Item type: Other Journal Item
    Chautems, Christophe; Zeydan, Burak; Charreyron, Samuel; et al. (2017)
    European Journal of Cardio-Thoracic Surgery
Publications 1 - 10 of 17