Abstract
The present chapter discusses the control design of MRI-guided robots in the vasculature to achieve targeted therapy through precise drug delivery. Such robots consist of a polymer-bonded aggregate of nanosized ferromagnetic and drug particles that can be propelled by the gradient coils of an MRI device. The feasibility of the concept has been largely studied in the literature, but few works address the nonlinear control issues related to a fine modeling of the forces acting on the magnetic microrobot. In this chapter, a fine modeling is developed with concerns about the constraints of the application. The notion of optimal trajectory derived from the nonlinear model is presented and shows that one can exploit the complexity of such a model to optimize the tracking performances. Then, different theoretical approaches to design nonlinear controllers with nonlinear observers are proposed, e.g., (a) Lyapunov controller with an adaptive backstepping law, (b) model predictive control (MPC), and (c) optimal control using linear quadratic integral (LQI) controller. The benefits of this fine modeling and the use of advanced control law and observer are illustrated by simulations and experimental results. Finally, perspectives and open problems in the field of MRI-guided robots’ control are discussed.
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References
Vartholomeos, P., Fruchard, M., Ferreira, A., & Mavroidis, C. (2011). MRI-guided Nanorobotic Systems for Therapeutic and Diagnostic Applications. Annual Review of Biomedical Engineering, 13, 157–184.
Folio, D., & Ferreira, A. (2017). 2D robust magnetic resonance navigation of a ferromagnetic microrobot using Pareto optimality. IEEE-Transactions on Robotics, 33(3), 583–593.
Gillies, G. T., Ritter, R. C., Broaddus, W. C., et al. (1994). Magnetic manipulation instrumentation for medical physics research. Review of Scientific Instruments, 65(3), 533–562.
Quate, E. G., Wika, K. G., Lawson, M. A., et al. (1991). Goniometric motion controller for the superconducting coil in a magnetic stereoaxis system. IEEE Transactions on Biomedical Engineering, 38, 899–905.
Takeda, S.-I., Mishima, F., Fujimoto, S., Izumi, Y., & Nishijima, S. (2006). Development of magnetically targeted drug delivery system using superconducting magnet. Journal of Magnetism and Magnetic Materials, 311, 367–371.
Mathieu, J., Beaudoin, G., & Martel, S. (2006). Method of propulsion of a ferromagnetic Core in the cardiovascular system through magnetic gradients generated by an MRI system. IEEE Transactions on Biomedical Engineering, 53(2), 292–299.
Mathieu, J.-B., & Martel, S. (2007). Magnetic microparticle steering within the constraints of an MRI system: Proof of concept of a novel targeting approach. Biomedical Microdevices, 9, 801–808.
Tamaz, S., Gourdeau, R., Chanu, A., Mathieu, J.-B., & Martel, S. (2008). Real-time MRI-based control of a ferromagnetic Core for endovascular navigation. IEEE Transactions on Biomedical Engineering, 55(7), 1854–1863.
Martel, S., Mathieu, J.-B., Felfoul, O., et al. (2007). Automatic navigation of an untethered device in the artery of a living animal using a conventional clinical magnetic resonance imaging system. Applied Physics Letters, 90(11), 114105.
Yesin, K. B., Vollmers, K., & Nelson, B. J. (2006). Modeling and control of untethered biomicrorobots in a fluidic environment using electromagnetic fields. International Journal of Robotics Research, 25, 527–536.
Jun, Y.-W., Seo, J.-W., & Cheon, J. (2007). Nanoscaling laws of magnetic nanoparticles and their applicabilities in biomedical sciences. Accounts of Chemical Research, 41(2), 179–189.
Dreyfus, R., Beaudry, J., Roper, M. L., et al. (2005). Microscopic artificial swimmers. Nature, 437(6), 862–865.
Behkam, B., & Sitti, M. (2006). Design methodology for biomimetic propulsion of miniature swimming robots. ASME Journal of Dynamic Systems, Measurement and Control, 128, 36–43.
Yesin, K. B., Vollmers, K., & Nelson, B. J. (2004). Analysis and design of wireless magnetically guided microrobots in body fluids. In Proceedings of the IEEE international conference on robotics and automation, New Orleans, USA (pp. 1333–1338).
Abbott, J. J., Peyer, K. E., Lagomarsino, M. C., et al. (2007). How should microrobots swim? In International symposium on robotics research.
Lee, H., Purdon, A. M., Chu, V., & Westervelt, R. M. (2004). Controlled assembly of magnetic nanoparticles from magnetotactic bacteria using microelectromagnets arrays. Nano Letters, 4(5), 995–998.
Martel, S., Mohammadi, M., Felfoul, O., Lu, Z., & Pouponneau, P. (2009). Flagellated magnetotactic bacteria as controlled MRI-trackable propulsion and steering systems for medical nanorobots operating in the human microvasculature. The International Journal of Robotics Research, 28(4), 571–582.
Martel, S., Tremblay, C. C., Ngakeng, S., & Langois, G. (2006). Controlled manipulation and actuation of micro-objects with magnetotactic bacteria. Applied Physics Letters, 89(23), 233904.
Plowman, S. A., & Smith, D. L. (1997). Exercise physiology. Needham Heights: Allyn and Bacon.
White, F. (1991). Viscous fluid flow. New York: McGraw Hill.
Kehlenbeck, R., & Di Felice, R. (1999). Empirical relationships for the terminal settling velocity of spheres in cylindrical columns. Chemical Engineering & Technology, 21, 303–308.
Francis, A. W. (1933). Wall effect in falling ball method for viscosity. Physics, 4, 403–406.
Munroe, H. S. (1888). The English versus the continental system of jigging is close sizing advantageous? Transactions of the American Institute of Mining, Metallurgical, and Petroleum Engineers, 17.
Tijskens, E., Ramon, H., & De Baerdemaeker, J. (2003). Discrete element for process simulation in agriculture. Journal of Sound and Vibration, 266, 493–514.
Varthomoleos, P., & Mavroidis, C. (2020). Magnetic targeting of aggregated nanoparticles for advanced lung therapies: A robotics approach. In: 3rd IEEE International Conference on Biomedical Robotics and Biomechatronics, 26–29 September 2010, Tokyo, Japan.
Hays, D. (1991). Electrostatic adhesion of non-uniformly charged dielectric sphere. International Physis Conference Series, 118, 223–228.
Hays, D. (1991). Role of electrostatics in adhesion, in fundamentals of adhesion. PLENUMPRESS.
Arcese, L., Fruchard, M., & Ferreira, A. (2012). Endovascular magnetically-guided robots: Navigation modeling and optimization. IEEE-Transactions on Biomedical Engineering, 59(4), 977–987.
Belharet, K., Folio, D., & Ferreira, A. (2013, April). Simulation and planning of a magnetically actuated microrobot navigating in the arteries. IEEE-Transactions on Biomedical Engineering, 60(4), 993–1001.
Arcese, L., Fruchard, M., & Ferreira, A. (2013). Adaptive controller and observer for a magnetic microrobot. IEEE-Transactions on Robotics, 29(4), 1060–1067.
Sadelli, L., Fruchard, M., & Ferreira, A. (May 2017). 2D observer-based control of a vascular microrobot. IEEE-Transactions on Automatic Control, 62(5), 2194–2206.
Clarke, D., Mohtadi, C., & Tuffs, P. (1987). Generalized predictive control – part I & II. Automatica, 23, 137–160.
Belharet, K., Folio, D., & Ferreira, A. (2011, May). 3D controlled motion of a microrobot using magnetic gradients. Advanced Robotics, 25(8), 1069–1083.
Belharet, K., Folio, D., & Ferreira, A. (2020) Endovascular Navigation of Ferromagnetic Microrobot using MRI-based Predictive Control. In IEEE International Conference on Intelligent Robots and Systems (IROS’10), Taipei, Taiwan, October 18–22, 2010, pp. 2804–2809.
Shin, J., Nonami, K., Fujiwara, D., & Hazawa, K. (2005). Model-based optimal attitude and positioning control of small-scale unmanned helicopter. Robotica, 23(01), 51–63.
Seto, K., Fuji, D., Hiramathu, H., & Watanabe, T. (2002). Motion and vibration control of three dimensional flexible shaking table using LQI control approach. In Proceedings of American control conference (Vol. 4, pp. 3040–3045). IEEE.
Mellal, L., Folio, D., Belharet, K., & Ferreira, A. (2016). Optimal Control of Multiple Magnetic Microbeads Navigating in Microfluidic Channels. In IEEE International Conference on Robotics and Automation (ICRA16), Stockholm, Sweden, May 16–21, 2016.
Arcese, L., Fruchard, M., & Ferreira, A. (2009). Nonlinear modeling and robust controller-observer for a magnetic microrobot in a fluidic environment using MRI gradients. IROS.
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Ferreira, A. (2022). Fundamentals and Field-Driven Control of Micro-/Nanorobots. In: Sun, Y., Wang, X., Yu, J. (eds) Field-Driven Micro and Nanorobots for Biology and Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-80197-7_1
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