The Simulation and Path Tracking Control Study of Magnetic Miniature Soft Robots

Abstract

Magnetic miniature soft robots hold significant potential in biomedical research, especially for targeted therapy, drug delivery, and cell manipulation. Precise path tracking control is crucial for these robots in complex biomedical applications. Here, we propose a Stanley path tracking control algorithm based on visual feedback for magnetic soft robots. First, a magnetic miniature soft crawling robot was designed and fabricated, and its crawling mechanism was detailed. Next, a simulation framework using the material point method (MPM) was constructed to simulate the movement and deformation of the miniature robot and to verify the proposed crawling mechanism. Finally, visual feedback technology was used to obtain the robot's position and posture, and the Stanley algorithm was applied for path tracking control in crawling mode. The effectiveness of the proposed path tracking control strategy has been verified through multiple experiments. Compared with the traditional Pure Pursuit control method, it has higher robustness and better control accuracy.