AI-Driven Robotics for Optics

TL;DR

This paper presents a novel AI-driven robotic platform that automates the design, assembly, and alignment of optical experiments, significantly enhancing throughput, precision, and reproducibility in optical science research.

Contribution

The work introduces the first flexible, AI-integrated automation system for optics that translates goals into configurations, assembles components, and performs measurements autonomously.

Findings

Automation surpasses human consistency in optical measurements.

Platform enables remote operation and high-throughput optical experiments.

Demonstrates successful execution of beam characterization, polarization mapping, and spectroscopy.

Abstract

Optics is foundational to research in many areas of science and engineering, including nanophotonics, quantum information, materials science, biomedical imaging, and metrology. However, the design, assembly, and alignment of optical experiments remain predominantly manual, limiting throughput and reproducibility. Automating such experiments is challenging due to the strict, non-negotiable precision requirements and the diversity of optical configurations found in typical laboratories. Here, we introduce a platform that integrates generative artificial intelligence, computer vision, and robotics to automate free-space optical experiments. The platform translates user-defined goals into valid optical configurations, assembles them using a robotic arm, and performs micrometer-scale fine alignment using a robot-deployable tool. It then executes a range of automated measurements, including beam characterization, polarization mapping, and spectroscopy, with consistency surpassing that of human operators. This work demonstrates the first flexible, AI-driven automation platform for optics, offering a path towards remote operation, cloud labs, and high-throughput discovery in the optical sciences.