Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 118, Issue 21, Pages -Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2021922118
Keywords
magnetic soft continuum robot; workspace; hard-magnetic elastica; finite difference method; genetic algorithm
Categories
Funding
- Massachusetts Institute of Technology
- Centers for Mechanical Engineering Research and Education at Massachusetts Institute of Technology
- Southern University of Science and Technology
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A new design and optimization method for a novel magnetic soft continuum robot is reported, using nonuniform distribution of magnetic particles to achieve an optimal workspace. This method integrates theoretical models and genetic algorithms, providing a powerful tool for the design of future magnetic soft robots and actuators.
Worldwide cardiovascular diseases such as stroke and heart disease are the leading cause of mortality. While guidewire/catheter-based minimally invasive surgery is used to treat a variety of cardiovascular disorders, existing passive guidewires and catheters suffer from several limitations such as low steerability and vessel access through complex geometry of vasculatures and imaging-related accumulation of radiation to both patients and operating surgeons. To address these limitations, magnetic soft continuum robots (MSCRs) in the form of magnetic field-controllable elastomeric fibers have recently demonstrated enhanced steerability under remotely applied magnetic fields. While the steerability of an MSCR largely relies on its workspace-the set of attainable points by its end effector- existing MSCRs based on embedding permanent magnets or uniformly dispersing magnetic particles in polymer matrices still cannot give optimal workspaces. The design and optimization of MSCRs have been challenging because of the lack of efficient tools. Here, we report a systematic set of model-based evolutionary design, fabrication, and experimental validation of an MSCR with a counterintuitive nonuniform distribution of magnetic particles to achieve an unprecedented workspace. The proposed MSCR design is enabled by integrating a theoretical model and the genetic algorithm. The current work not only achieves the optimal workspace for MSCRs but also provides a powerful tool for the efficient design and optimization of future magnetic soft robots and actuators.
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