3D Flexible Locomotion of Magnetic Soft Flapping Milliswimmers Based on Adaptive MPC

Magnetic soft flapping milliswimmers hold significant potential for biomedical applications due to their flexible mobility and multifunctionality. However, advanced motion control tasks for such forms remain underexplored, hindering their flexible mobility and various biomedical applications. The multi-physics coupling inherent in the flapping swimming process presents substantial challenges for dynamics modeling and control. In this study, we fabricated a magnetic soft flapping millirobot and conducted dynamics analysis using rigid-body modeling and quasi-static wing-flapping analysis method. The resulting state-space model is employed to build a navigation control framework based on adaptive Model Predictive Control (MPC) method, realizing autonomous navigation and obstacle avoidance performances. To validate the effectiveness of the proposed control framework, the complex path-following task in 3D space is performed, demonstrating superior performance compared to geometry-based following methods. Furthermore, the robot’s navigation ability in complex environments is evaluated in both physical and simulated setups featuring static and dynamics obstacles. The milliswimmer’s 3D flexible mobility and its capability to operate effectively in challenging and intricate environments may reveal great potential for real-world biomedical and other advanced applications. Note to Practitioners—This paper is motivated by the problem of precise motion control task of the magnetic soft flapping milliswimmer but the method also applies to other magnetic torque driven swimmers. Existing literature has not fully investigated the modeling and control strategy for the magnetic driven flapping swimming motion. This paper suggests a modeling method to describe the magnetic field driven propulsion from body-environment interactions and proposed a control framework which is suitable for the mechanism. We then demonstrate the efficacy of the method with a series of experiments on advanced motion control tasks. In future research, we will explore how instantaneous magnetic actuation dynamics shape the robot’s motion profile, with the goal of improving both the generalization capability and precision of the proposed approach.