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Hard-magnetic elastica
Abstract
Abstract Recently, ferromagnetic soft continuum robots – a type of slender, thread-like robots that can be steered magnetically – have demonstrated the capability to navigate through the brain's narrow and winding vasculature, offering a range of captivating applications such as robotic endovascular neurosurgery. Composed of soft polymers with embedded hard-magnetic particles as distributed actuation sources, ferromagnetic soft continuum robots produce large-scale elastic deflections through magnetic torques and/or forces generated from the intrinsic magnetic dipoles under the influence of external magnetic fields. This unique actuation mechanism based on distributed intrinsic dipoles yields better steering and navigational capabilities at much smaller scales, which differentiate them from previously developed continuum robots. To account for the presence of intrinsic magnetic polarities, this emerging class of magnetic continuum robots provides a new type of active structure – hard-magnetic elastica – which means a thin, elastic strip or rod with hard-magnetic properties. In this work, we present a nonlinear theory for hard-magnetic elastica, which allows accurate prediction of large deflections induced by the magnetic body torque and force in the presence of an external magnetic field. From our model, explicit analytical solutions can be readily obtained when the applied magnetic field is spatially uniform. Our model is validated by comparing the obtained solutions with both experimental results and finite element simulations. The validated model is then used to calculate required magnetic fields for the robot's end tip to reach a target point in space, which essentially is an inverse problem challenging to solve with a linear theory or finite-element simulation. Providing facile routes to analyze nonlinear behavior of hard-magnetic elastica, the presented theory can be used to guide the design and control of the emerging class of magnetically steerable soft continuum robots.
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Cited by
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Zhao, X., Chen, X., Yuk, H., Lin, S., Liu, X., & Parada, G. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01088 · Cited by 1,161
Self-citationMagnetic Soft Materials and Robots
Kim, Y., & Zhao, X. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00481 · Cited by 873
Self-citationTelerobotic neurovascular interventions with magnetic manipulation
Kim, Y., Genevriere, E., Harker, P., Choe, J., Balicki, M., Regenhardt, R. W., Vranic, J. E., Dmytriw, A. A., Patel, A. B., & Zhao, X. (2022) · Science Robotics · doi:10.1126/scirobotics.abg9907 · Cited by 422
Self-citationFerromagnetic soft catheter robots for minimally invasive bioprinting
Zhou, C., Yang, Y., Wang, J., Wu, Q., Gu, Z., Zhou, Y., Liu, X., Yang, Y., Tang, H., Ling, Q., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25386-w · Cited by 242
Self-citationMagnetic soft microfiberbots for robotic embolization
Liu, X., Wang, L., Xiang, Y., Liao, F., Li, N., Li, J., Wang, J., Wu, Q., Zhou, C., Yang, Y., et al. (2024) · Science Robotics · doi:10.1126/scirobotics.adh2479 · Cited by 213
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Metadata
- Authors
- Wang, L., Kim, Y., Guo, C. F., & Zhao, X.
- Venue
- Journal of the Mechanics and Physics of Solids
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 142
- Pages
- 104045
- ISSN
- 0022-5096 (ISSN-L)
- OpenAlex
- W3033268204
- Cited by
- 251
- References
- 0
- FWCI
- 8.55
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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