A unified optimization strategy for the geometry and magnetization of magnetic soft continuum robots in vascular intervention

Abstract

Magnetic soft continuum robots (MSCRs) can actively deflect under external magnetic fields, enabling navigation through complex vascular systems and guiding surgical instruments to hard-to-reach pathological areas. The navigation capability and steerability of MSCRs mainly depend on the bending angle of the distal end. In this work, we present a unified optimization strategy for MSCRs, sequentially optimizing both geometry and magnetization. The optimized MSCR achieves a larger bending angle, enhancing selective navigation in narrow vascular environments. First, a finite difference model is developed to describe the deformation of MSCRs under external fields. Then, the Gray Wolf Optimizer and the Modified Discrete Gray Wolf Optimizer are employed to optimize geometry and magnetization. The effectiveness of the proposed strategy is verified through theoretical calculations and deflection experiments. Additionally, selective navigation in a 2D planar model and targeted navigation in a 3D human vascular model demonstrate the superior steerability and flexibility of the optimized MSCR.