Smart navigation of microswimmers in Poiseuille flow via reinforcement learning.

Authors

Priyam Chakraborty, Rahul Roy, Shubhadeep Mandal

Published in

The European physical journal. E, Soft matter. Volume 48. Issue 6-7. Pages 30. Jun 12, 2025. Epub Jun 12, 2025.

Abstract

Artificial microswimmers, such as active colloids, have the potential to revolutionize targeted drug delivery, but controlling their motion under imposed flow conditions remains challenging. In this work, we implement reinforcement learning (RL) to control the navigation of a microswimmer in a plane Poiseuille flow, with applications in targeted drug delivery. With RL, the swimmer learns to efficiently reach its target by continuously adjusting its swinging or tumbling behavior depending upon its self-propulsion strength, chirality and the imposed flow strength. This RL-based approach enables precise control of the particle's path, achieving reliable targeting even in stringent scenarios such as upstream motion in high bulk flow, thus advancing the design of intelligent in vivo medical microrobots.

PMID:
40504448
Bibliographic data and abstract were imported from PubMed on 12 Jun 2025.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.