Acta Photonica Sinica, Volume. 47, Issue 1, 112001(2018)

High Precision Calibration Model of Laser 3D Projection

GUO Li-li1、*, LI Li-juan1, QIAO Xiao-li2, HOU Mao-sheng1, and LIN Xue-zhu1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    In order to improve the calibration reliability of laser 3D projection calibration system and to obtain the best calibration parameters, according to the basic principle of the system, a method is proposed to combine the laser 3D projection observation model with the calibration parameter solution model to build a laser 3D projection calibration model approach. The method uses two steps to solve the calibration parameter of laser 3D projection calibration system. The first step is to establish the solution model of laser 3D projection observation by the isometric method, and to introduce the solution of the initial value of the model. The design results of this initial value avoid the drawbacks of the Newton iterative method. In the second step, the quaternion method is used to establish the model of the calibration parameters. The simulation results show that the error of the 3D projection calibration system is less than 0.3 mm when the mean value of the normal distribution is 0 and the standard deviation is 0.5″.At the same time, the laser tracker system is used as a benchmark to verify the calibration precision and reliability of the method. The results show that the maximum error is within 0.4 mm in the range of 3 to 5 m, which meets the projection of laser 3D projection system positioning accuracy. The calibration model can realize the calibration of the laser 3D projection calibration system, and the calibration precision is high and the calibration method converges fast and improves the system calibration rate which provides a new algorithm for the development of laser projection system.

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    GUO Li-li, LI Li-juan, QIAO Xiao-li, HOU Mao-sheng, LIN Xue-zhu. High Precision Calibration Model of Laser 3D Projection[J]. Acta Photonica Sinica, 2018, 47(1): 112001

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    Paper Information

    Received: Jun. 2, 2017

    Accepted: --

    Published Online: Jan. 30, 2018

    The Author Email: Li-li GUO (custlily@163.com)

    DOI:10.3788/gzxb20184701.0112001

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