Chia-Wei Chen,1,2 Bowen Zhou,1 Thomas Längle,2 Jürgen Beyerer1,2
1Vision and Fusion Lab. (IES), Karlsruhe Institute of Technology (KIT) (Germany) 2Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB (Germany)
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Tolerance analysis and tolerance sensitivity optimization (desensitization) are important and necessary for manufacturability. However, compared to the optimization of optical performance, tolerance analysis is still time-consuming. A machine learning approach for the fast robustness estimation of lens systems is proposed. The results of the machine learning estimation and the other four different methods are compared with the results of the Monte Carlo analysis. The proposed model is added to the merit function in commercial software for optimization to reduce the sensitivity.
Chia-Wei Chen,Bowen Zhou,Thomas Längle, andJürgen Beyerer
"Robustness estimation of simple lens systems by machine learning", Proc. SPIE 12078, International Optical Design Conference 2021, 120781B (19 November 2021); https://doi.org/10.1117/12.2603658
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Chia-Wei Chen, Bowen Zhou, Thomas Längle, Jürgen Beyerer, "Robustness estimation of simple lens systems by machine learning," Proc. SPIE 12078, International Optical Design Conference 2021, 120781B (19 November 2021); https://doi.org/10.1117/12.2603658