Surface-topography-guided locomotion of magnetic microbots enabled by vision-based adaptive control

Microbots offer transformative potential for targeted biomedicine, yet their controlled navigation across heterogeneous biological environments remains challenging. While the effects of spatial confinement and fluid properties on microbot dynamics are well studied, the critical role of surface microtopography remains underexplored. Here, we investigate how surface microtopography affects the motion of microellipsoids with different aspect ratios when actuated by time-varying magnetic fields. On patterned surfaces with periodic peaks and valleys, hydrodynamic coupling between the rotating particle and the boundary impacts the translation-rotation interplay in response to local topography. These topographic features enhance traction and improve locomotion compared to smooth substrates. We further implement a vision-based feedback control scheme that maps surface topography in real time and selectively guides microellipsoids across hybrid surfaces by altering external field parameters. By coupling real-time surface recognition with adaptive control, this work demonstrates a strategy for enabling semi-autonomous navigation of microbots across heterogeneous terrains.