• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2026, Vol. 62 ›› Issue (15): 382-396.doi: 10.3901/JME.260828

Previous Articles    

Path Following Control of Cone-helical Swimming Magnetic Microrobots

LI Pan1,2, YE Chongcong1, CHEN Yifei1, FANG Delei1, ZHANG Junxia1, LIANG Cunman2,3   

  1. 1. Tianjin Key Laboratory of Integrated Design and On-line Monitoring for Light Industry & Food Machinery and Equipment, Tianjin University of Science and Technology, Tianjin 300457;
    2. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300354;
    3. State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074
  • Received:2025-08-31 Revised:2025-12-15 Published:2026-10-13

Abstract: In minimally invasive vascular interventional surgery, the intervention process relies on the doctor’s experiential operations and inevitably encounters issues with restricted operations in highly curved blood vessels. This research introduces a cone-helical swimming magnetic microrobot and investigates its path-following control strategy, achieving automation in the operation process of the microrobot. An enhanced A* path planning algorithm is developed, taking into account blood clots as obstacles in the vessels, by expanding them to generate globally optimal paths with continuous curvature. A dual closed-loop control strategy based on visual extraction is established, integrating fuzzy control principles with the Stanley algorithm and model predictive control (MPC) algorithm to accomplish outer-loop path-following control, providing ideal motion state parameters. Inner-loop steering control is achieved using PI control to output external magnetic field parameters. Path-following simulations are conducted in S-shaped and U-shaped blood vessel environments with blood clots, analyzing the impact of different initial errors and motion speeds on path-following effectiveness. The simulation results show that combining the Stanley algorithm with the MPC algorithm based on fuzzy control helps to eliminate the oscillations that occur during tracking with the Stanley algorithm, resulting in smoother tracking. This fusion decreases errors in steering associated with the MPC algorithm, and improves both tracking speed and accuracy. Deceleration is applied at steering positions, reducing errors by 37.5% compared to constant-speed motion. Path-following control experiments in simulated blood vessels validate the feasibility of automated control of the magnetic microrobot in practical applications.

Key words: vascular interventional surgery, magnetically driven, helical microrobot, path planning, path tracking, automatic control

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