Artificial intelligence inspired freeform optics design: a review

TL;DR

This review discusses how artificial intelligence techniques like machine learning and deep learning are revolutionizing freeform optics design by improving efficiency, expanding possibilities, and enabling innovative solutions, despite existing challenges.

Contribution

It provides a comprehensive overview of recent AI applications in freeform optics, highlighting their roles, benefits, and future research directions in this field.

Findings

AI enhances design efficiency and accuracy.

AI expands the design space and enables innovative solutions.

Challenges include data needs and model interpretability.

Abstract

Integrating artificial intelligence (AI) techniques such as machine learning and deep learning into freeform optics design has significantly enhanced design efficiency, expanded the design space, and led to innovative solutions. This article reviews the latest developments in AI applications within this field, highlighting their roles in initial design generation, optimization, and performance prediction. It also addresses the benefits of AI, such as improved accuracy and performance, alongside challenges like data requirements, model interpretability, and computational complexity. Despite these challenges, the future of AI in freeform optics design looks promising, with potential advancements in hybrid design methods, interpretable AI, AI-driven manufacturing, and targeted research for specific applications. Collaboration among researchers, engineers, and designers is essential to fully harness AI's potential and drive innovation in optics.