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Chinese Optics, Volume. 16, Issue 2, 407(2023)

Positioning algorithm for laser spot center based on BP neural network and genetic algorithm

Jing-yuan ZHANG1,2, Bei-bei CHEN1,2, Yong-xing YANG1,2, Qing-sheng ZHU1,2,3, Jin-peng LI1,2,3, and Jin-biao ZHAO3
Author Affiliations
  • 1University of Science and Technology of China, Hefei 230022, China
  • 2Nanjing Research Center of Astronomical Instruments, University of Science and Technology of China, Nanjing 210042, China
  • 3Nanjing Astronomical Instruments Co., Ltd., Chinese Academy of Sciences, Nanjing 210042, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (13)
    Equations (5)
    References (23)
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    Figures & Tables(13)
    Flow chart of genetic algorithm combined with BP neural network

    Fig. 1. Flow chart of genetic algorithm combined with BP neural network

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    Structure of traditional BP neural network

    Fig. 2. Structure of traditional BP neural network

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    Structure of the proposed neural network model

    Fig. 3. Structure of the proposed neural network model

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    Experimental hardware platform

    Fig. 4. Experimental hardware platform

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    The vibration curves along x-axis for the spot center

    Fig. 5. The vibration curves along x-axis for the spot center

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    Laser spot image

    Fig. 6. Laser spot image

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    Training curve of BP neural network

    Fig. 7. Training curve of BP neural network

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    Training curve of GA-BP neural network

    Fig. 8. Training curve of GA-BP neural network

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    Performance comparison of two network prediction methods

    Fig. 9. Performance comparison of two network prediction methods

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    The vibration curves along x-axis for the spot center under controlling

    Fig. 10. The vibration curves along x-axis for the spot center under controlling

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    • Table 1. Training data

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      Table 1. Training data

      Grayscale centering centroidGaussian fitting radiusActual Coordinate
      (252.30, 305.11) (255.43, 309.27) (254.17, 307,91) 7(253.30, 307,11)

    • Table 2. Performance comparison of the two neural networks

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      Table 2. Performance comparison of the two neural networks

      Neural NetworkBPGA-BP
      Number of iterations5529
      Mean error/pixel0.760.42

    • Table 3. Performance test results by the two neural networks

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      Table 3. Performance test results by the two neural networks

      Neural NetworkBPGA-BP
      Number of iterations4732
      Mean error/pixel1.210.73
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    Jing-yuan ZHANG, Bei-bei CHEN, Yong-xing YANG, Qing-sheng ZHU, Jin-peng LI, Jin-biao ZHAO. Positioning algorithm for laser spot center based on BP neural network and genetic algorithm[J]. Chinese Optics, 2023, 16(2): 407

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    Paper Information

    Category: Original Article

    Received: Apr. 28, 2022

    Accepted: Aug. 24, 2022

    Published Online: Apr. 4, 2023

    The Author Email:

    DOI:10.37188/CO.2022-0084

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