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How Should Microrobots Swim?

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland, Department of Mechanical Engineering, University of Utah, Salt Lake City, UT 84112, USA, jake.abbott{at}utah.edu

Kathrin E. Peyer

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland

Marco Cosentino Lagomarsino

Department of Physics, University of Milan, 20133 Milan, Italy

Li Zhang

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland

Lixin Dong

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland, Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA

Ioannis K. Kaliakatsos

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland

Bradley J. Nelson

Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland

Microrobots have the potential to dramatically change many aspects of medicine by navigating through bodily fluids to perform targeted diagnosis and therapy. Researchers have proposed numerous micro-robotic swimming methods, with the vast majority utilizing magnetic fields to wirelessly power and control the microrobot. In this paper, we compare three promising methods of microrobot swimming (using magnetic fields to rotate helical propellers that mimic bacterial flagella, using magnetic fields to oscillate a magnetic head with a rigidly attached elastic tail, and pulling directly with magnetic field gradients) considering practical hardware limitations in the generation of magnetic fields. We find that helical propellers and elastic tails have very comparable performance, and they generally become more desirable than gradient pulling as size decreases and as distance from the magnetic-field-generation source increases. We provide a discussion of why helical propellers are likely the best overall choice for in vivo applications.

Key Words: microrobot • magnetic • wireless • untethered • medical • in vivo

This version was published on November 1, 2009

The International Journal of Robotics Research, Vol. 28, No. 11-12, 1434-1447 (2009)
DOI: 10.1177/0278364909341658


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