Reinforcement learning of a biflagellate model microswimmer

2025/08/21 by Bulusu, Sridhar, Zöttl, Andreas · 1 citation
#Biological Physics (physics.bio-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Soft Condensed Matter (cond-mat.soft)

paper · doi:10.48550/arxiv.2508.15561

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.

Citations

• Enabling microrobotic chemotaxis via reset-free hierarchical reinforcement learning
• Bacterial active matter
• Optimal Strokes of Low Reynolds Number Linked-Sphere Swimmers
• Physics of microswimmers—single particle motion and collective behavior: a review
• Metachronal waves in a chain of rowers with hydrodynamic interactions
• The hydrodynamics of swimming microorganisms
• Fluid Mechanics of Propulsion by Cilia and Flagella

Cited by

• Optimal Undulatory Swimming with Constrained Deformation and Actuation Intervals

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