Can flocking aid the path planning of microswimmers in turbulent flows?
Abstract
We show that flocking of microswimmers in a turbulent flow can enhance the efficacy of reinforcement-learning-based path-planning of microswimmers in turbulent flows. In particular, we develop a machine-learning strategy that incorporates Vicsek-model-type flocking in microswimmer assemblies in a statistically homogeneous and isotropic turbulent flow in two dimensions (2D). We build on the adversarial-reinforcement-learning of Ref.~\cite{alageshan2020machine} for non-interacting microswimmers in turbulent flows. Such microswimmers aim to move optimally from an initial position to a target. We demonstrate that our flocking-aided version of the adversarial-reinforcement-learning strategy of Ref.~\cite{alageshan2020machine} can be superior to earlier microswimmer path-planning strategies.
Cite
@article{arxiv.2411.15902,
title = {Can flocking aid the path planning of microswimmers in turbulent flows?},
author = {Akanksha Gupta and Jaya Kumar Alageshan and Kolluru Venkata Kiran and Rahul Pandit},
journal= {arXiv preprint arXiv:2411.15902},
year = {2024}
}