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AI-driven robotics for optics.

Created on 20 Aug 2026

Authors

Shiekh Zia Uddin, Sachin Vaidya, Shrish Choudhary, Zhuo Chen, Raafat K Salib, Luke Huang, Dirk R Englund, Marin Soljačić

Published in

Science advances. Volume 12. Issue 34. Pages eaee1381. Aug 21, 2026. Epub Aug 19, 2026.

Abstract

Optical experiments are essential across science and technology, yet their design, assembly, and alignment remain predominantly manual, limiting throughput, reproducibility, and scalability. Automating such experiments is challenging because of stringent precision requirements and the diversity of setups in typical real-world optical laboratory environments. Here, we introduce a platform that integrates generative artificial intelligence, computer vision, and precision robotics to automate free-space optical experiments. The system translates user-defined goals into valid optical configurations, assembles them with submillimeter accuracy, and performs micrometer-scale fine alignment using a robotic tool. It then executes a range of accurate measurements, including beam characterization, polarization mapping, and spectroscopy. This work establishes a platform for reconfigurable optics automation, potentially enabling programmable and adaptive experimental workflows.

PMID:
42616899
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.

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