Autonomous Navigation of Magnetic Microrobots in a Large Workspace Using Mobile-Coil System

Untethered magnetic miniature robots have attracted much attention in recent years, due to their minimally invasive features in biomedicine and highly flexible traits in micromanipulation. Autonomous control is one of the essential issues for magnetic microrobots, however, which remains challenging, especially for complex and large-workspace environments. To this end, this article proposes a novel navigation framework, using a home-designed eye-in-hand mobile-coil system. A three-step motion planner is designed to know entire surroundings and generate optimal paths, which contains environment reconstruction, position registration, and modified A∗ path searching. Moreover, a double-loop motion controller is designed to make the microrobot accurately follow the computed path and intelligently avoid collisions: The inner loop performs mechanism following; the outer loop decides appropriate magnetic fields for actuation, which includes a disturbance observer (DOB), a fuzzy logic modifier (FLM), and a model predictive controller (MPC). Experiments demonstrate the effectiveness of the proposed strategy: Feasible trajectories in a maze-like environment of diameter 230 mm can be planned, and autonomous navigation of microrobot is realized with both global accessibility and local adaptability.