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Fast path planning algorithm for large-aperture aspheric optical elements based on minimum object depth and a

Fanyi Wang, Yongying Yang, Weiming Lou

    Applied Optics
    |April 26, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a fast path planning algorithm for inspecting large-aperture aspheric optical elements. The method ensures minimal object depth and optimizes overlap coefficients for efficient surface defect detection.

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    Area of Science:

    • Optical Engineering
    • Metrology
    • Machine Vision

    Background:

    • Surface defect detection of large-aperture aspheric optical elements requires full coverage inspection via scanning.
    • Efficient path planning is challenging due to continuously changing surface curvature.
    • Limited depth of field in machine vision systems causes out-of-focus blur, necessitating minimal object depth.

    Purpose of the Study:

    • To propose a fast path planning algorithm for sub-aperture imaging of aspheric optical elements.
    • To address challenges in path planning, object depth control, and overlap coefficient determination.
    • To achieve accurate surface defect detection with high reconstruction accuracy.

    Main Methods:

    • A fast path planning algorithm based on minimum object depth is proposed.
    • Images are collected along the normal direction of the sub-aperture plane to ensure minimum object depth.
    • An image processing-based overlap coefficient self-optimization algorithm is developed to handle varying surface curvatures.

    Main Results:

    • The algorithm achieves path planning in under 5 seconds.
    • Experimental results show a maximum stitching misalignment error of four pixels and an average of one pixel.
    • The developed algorithm enables automatic sub-aperture acquisition and reconstruction.

    Conclusions:

    • The proposed algorithm provides an efficient and accurate solution for path planning in aspheric optical element inspection.
    • The method effectively minimizes object depth and optimizes overlap coefficients for improved defect detection.
    • The reconstruction accuracy meets the requirements for subsequent image processing and digital quantization.