Liu Yuhang, Wang Jiahang, Lu Xiwen, Zhu Yunlong, Bai Chenyao
Academy for Engineering and Technology, Fudan University, 220 Handan Road Yangpu District, Shanghai 200433, China.
iScience. 2025 Apr 21;28(5):112419. doi: 10.1016/j.isci.2025.112419. eCollection 2025 May 16.
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.
磁性软连续体机器人（MSCRs）能够在外部磁场作用下主动弯曲，从而实现通过复杂血管系统的导航，并将手术器械引导至难以触及的病理区域。MSCRs的导航能力和可操纵性主要取决于其远端的弯曲角度。在这项工作中，我们提出了一种针对MSCRs的统一优化策略，依次对几何形状和磁化进行优化。优化后的MSCR实现了更大的弯曲角度，增强了在狭窄血管环境中的选择性导航能力。首先，建立了一个有限差分模型来描述MSCRs在外部磁场作用下的变形。然后，采用灰狼优化器和改进的离散灰狼优化器对几何形状和磁化进行优化。通过理论计算和偏转实验验证了所提策略的有效性。此外，在二维平面模型中的选择性导航和在三维人体血管模型中的靶向导航证明了优化后的MSCR具有卓越的可操纵性和灵活性。
