PINN予測による複雑流体中磁気マイクロロボットの流れ考慮型ナビゲーション
Flow-Aware Navigation of Magnetic Micro-Robots in Complex Fluids via PINN-Based Prediction
物理情報ニューラルネットワーク(PI-UNet)で流体速度を予測し、それをA*経路計画と制御に組み込むことで、複雑な流れの中での磁気マイクロロボットの精密なナビゲーションを実現した研究。
著者: Yongyi Jia, Shu Miao, Jiayu Wu, Ming Yang, Chengzhi Hu, Xiang Li
分類: cs.RO, cs.SY, eess.SY, physics.flu-dyn
原文アブストラクト
While magnetic micro-robots have demonstrated significant potential across various applications, including drug delivery and microsurgery, the open issue of precise navigation and control in complex fluid environments is crucial for in vivo implementation. This paper introduces a novel flow-aware navigation and control strategy for magnetic micro-robots that explicitly accounts for the impact of fluid flow on their movement. First, the proposed method employs a Physics-Informed U-Net (PI-UNet) to refine the numerically predicted fluid velocity using local observations. Then, the predicted velocity is incorporated in a flow-aware A* path planning algorithm, ensuring efficient navigation while mitigating flow-induced disturbances. Finally, a control scheme is developed to compensate for the predicted fluid velocity, thereby optimizing the micro-robot's performance. A series of simulation studies and real-world experiments are conducted to validate the efficacy of the proposed approach. This method enhances both planning accuracy and control precision, expanding the potential applications of magnetic micro-robots in fluid-affected environments typical of many medical scenarios.
