Reinforcement learning of a biflagellate model microswimmer
arXiv:2508.15561 · doi:10.1140/epje/s10189-025-00513-3
Abstract
Many microswimmers are able to swim through viscous fluids by employing periodic non-reciprocal deformations of their appendages. Here we use a simple microswimmer model inspired by swimming biflagellates which consists of a spherical cell body and two small spherical beads representing the motion of the two flagella. Using reinforcement learning we identify for different microswimmer morphologies quasi-optimized swimming strokes. For all studied cases the identified strokes result in symmetric and quasi-synchronized beating of the two flagella beads. Interestingly, the stroke-averaged flow fields are of pusher type, and the observed swimming gaits outperform previously used biflagellate microswimmer models relying on predefined circular flagella bead motion.
24 pages, 9 figures
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