ART of PIV: Agentic Real-Time Particle Image Velocimetry for Active Flow Control
Read the original on arXiv Computer Vision →The paper introduces ART of PIV, an automated system that selects the optimal particle image velocimetry pipeline configuration for each image pair based on a chosen measurement objective and speed budget. By dynamically choosing among cross‑correlation, classical optical‑flow, and learning‑based estimators, ART of PIV achieves 12.2‑22.4 % lower average end‑point error compared to the best single estimator at matched speed, and improves closed‑loop control performance in both simulated and physical experiments. The authors demonstrate the method on a simulated velocity regulation task and a tabletop water channel with a fluidic pinball, showing significant gains in accuracy and control effectiveness.
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