AI让自由曲面光学设计更高效，突破传统设计瓶颈。
Artificial intelligence inspired freeform optics design: a review
- 用机器学习生成初始光学结构，拓展设计空间。
- 提升设计精度与性能，实现复杂光学系统创新。
- 适合光学工程、AI交叉研究者参考。
将人工智能（AI）技术如机器学习和深度学习融入自由曲面光学设计，显著提升了设计效率，扩展了设计空间，并催生了创新解决方案。本文综述了该领域最新进展，重点阐述AI在初始设计生成、优化及性能预测中的作用。同时分析了其优势，如提高准确性和性能，也指出数据需求高、模型可解释性差和计算复杂度高等挑战。尽管存在困难，未来有望通过混合设计方法、可解释AI、AI驱动制造及特定应用研究实现突破。跨学科合作对充分发挥AI潜力、推动光学创新至关重要。
原文摘要 · Abstract (English)
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.
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