Decoupled Optimization of Position and Current in Electromagnet-Based Magnetic Navigation Systems for Magnetic Robot Manipulation

Magnetic robots actuated by magnetic navigation systems (MNSs) have been studied extensively in medical robotics. MNSs composed of multiple electromagnets (EMs) generate external magnetic fields required to apply torque and force to magnetic robots. However, the fixed EM positions in conventional MNSs hinder the generation of a strong magnetic field in the desired direction. To overcome this limitation, several MNSs have recently been proposed to mechanically control EM positions to maximize magnetic field generation. However, solving the resulting nonlinear problem with respect to EM position requires high computational cost. Here, we introduce a decoupled optimization method that first determines the optimal position of the magnetic robot in the ROI by moving the EM part and then determines the current applied to the MNS. The proposed method integrates particle swarm optimization and linear optimization to optimize the EM position and current combination, thereby maximizing both magnetic flux density and magnetic field gradient. Its effectiveness was verified by comparison with a conventional pseudoinverse method. We also experimentally validated the proposed method using an MNS with eight robotically adjustable EMs. Finally, the overall control process was evaluated through navigation experiments with a magnetic catheter and an untethered magnetic robot in various environments.