A Soft Magnetic Jamming Method Enabling Variable Stiffness and Active Steering for Robotic Catheter

Endovascular interventions demand catheters that can actively steer through tortuous vessels and dynamically increase stiffness at the target to ensure precise therapy. Most existing steerable catheters achieve steering and variable stiffness (VS) by multiple sources, leading to reduced efficiency advantage, increased bulkiness, and safety risks. This work introduces a magnetic jamming method that allows steering and VS using one magnetic source. First, a carrier-free, matrix-free magnetic jamming scheme is introduced that directly encapsulates soft-magnetic powder in coaxial thin-walled tubes, enabling single-source field-driven steering and reversible VS via interparticle jamming. Next, an analytical micro-to-macro stiffness model is established that explicitly links field parameters and particle properties to catheter-level outputs (i.e., stiffness and steering angle) by incorporating particle interaction, thus providing closed-form, physics-based estimations. Finally, we validate the method at both tip and catheter levels, confirming the stiffness model and substantial field-tunable stiffness modulation (up to 300-fold), with benchmarking against vacuum jamming as a reference to validate its effectiveness and demonstrating a multifunctional prototype that enables both steering and VS using a single magnetic source. Our magnetic jamming approach enables on-demand steering and rapid, large-range stiffness modulation in millimeter-scale catheters, promising faster navigation with lower contact forces, more stable device deployment, and a clearer path to autonomous, workflow-friendly endovascular interventions.

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Publication Details

Journal
Soft Robotics
Published
2026-06-12
DOI
https://doi.org/10.1177/21695172261459211
Primary Topic
Soft Robotics and Applications
Type
article
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article

A Soft Magnetic Jamming Method Enabling Variable Stiffness and Active Steering for Robotic Catheter

Qi Luo, Zhao Da, SW Cheng, Hongzhe Sun et al.
Soft Robotics
Soft Robotics and Applications
article

A Soft Magnetic Jamming Method Enabling Variable Stiffness and Active Steering for Robotic Catheter

Qi Luo, Zhao Da, SW Cheng, Hongzhe Sun, Liu Weikang
article en

Abstract

Endovascular interventions demand catheters that can actively steer through tortuous vessels and dynamically increase stiffness at the target to ensure precise therapy. Most existing steerable catheters achieve steering and variable stiffness (VS) by multiple sources, leading to reduced efficiency advantage, increased bulkiness, and safety risks. This work introduces a magnetic jamming method that allows steering and VS using one magnetic source. First, a carrier-free, matrix-free magnetic jamming scheme is introduced that directly encapsulates soft-magnetic powder in coaxial thin-walled tubes, enabling single-source field-driven steering and reversible VS via interparticle jamming. Next, an analytical micro-to-macro stiffness model is established that explicitly links field parameters and particle properties to catheter-level outputs (i.e., stiffness and steering angle) by incorporating particle interaction, thus providing closed-form, physics-based estimations. Finally, we validate the method at both tip and catheter levels, confirming the stiffness model and substantial field-tunable stiffness modulation (up to 300-fold), with benchmarking against vacuum jamming as a reference to validate its effectiveness and demonstrating a multifunctional prototype that enables both steering and VS using a single magnetic source. Our magnetic jamming approach enables on-demand steering and rapid, large-range stiffness modulation in millimeter-scale catheters, promising faster navigation with lower contact forces, more stable device deployment, and a clearer path to autonomous, workflow-friendly endovascular interventions.

Soft Robotics
Chinese University of Hong Kong (HK), Peking University (CN), Peking University First Hospital (CN), Nano and Advanced Materials Institute (CN)
Openalex Percentile: Top 11%
Soft Robotics and Applications
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