Artificial intelligence in optical lens design

Ai Ping Yow*, Damon Wong, Yueqian Zhang, Christoph Menke, Ralf Wolleschensky, Peter Török

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Traditional optical design entails arduous, iterative stages that significantly rely on the intuition and experience of lens designers. Starting-point design selection has always been the major hurdle for most optical design problem, and different designers might produce different final lens designs even if using the same initial specification. Lens designers typically choose designs from existing lens databases, analyse relevant lens structures, or explore patent literature and technical publications. With increased processing capability, producing automated lens designs using Artificial Intelligence (AI) approaches is becoming a viable alternative. Therefore, it is noteworthy that a comprehensive review addressing the latest advancements in using AI for starting-point design is still lacking. Herein, we highlight the gap at the confluence of applied AI and optical lens design, by presenting a comprehensive review of the current literature with an emphasis on using various AI approaches to generate starting-point designs for refractive optical systems, discuss the limitations, and suggest a potential alternate approach for further research.

Original languageEnglish
Article number193
JournalArtificial Intelligence Review
Volume57
Issue number8
DOIs
Publication statusPublished - Aug 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

ASJC Scopus Subject Areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

Keywords

  • Artificial intelligence
  • Deep learning
  • Expert system
  • Optical lens design
  • Reinforcement learning

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