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arXiv Machine Learning By Rajneesh Anand, Mayuresh V. Kothare

Autonomous Droplet Navigation via Model-Based Reinforcement Learning: Zero-Shot Transfer and Emergent Dynamics

Read the original on arXiv Machine Learning →

The paper presents a robotic platform that enables closed‑loop autonomous navigation of liquid droplets on an open surface using model‑based reinforcement learning. A two‑axis tilting board with a silicone oil film moves the droplet while an overhead camera supplies real‑time feedback, and a policy is trained in only 50–150 physical episodes without simulation or analytical models. The system demonstrates zero‑shot transfer to unseen geometries, autonomously discovers an oscillatory depinning strategy to release stuck droplets, and completes the full training pipeline in under 90 minutes.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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