• Optics and Precision Engineering
  • Vol. 32, Issue 6, 774 (2024)
Yaodong WANG1,2, Jinyang XU1,2,*, Liqiang ZHU1,2, Hongmei SHI1,2, and Yan FANG3
Author Affiliations
  • 1School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing00044, China
  • 2Frontiers Science Center for Smart High-Speed Railway System,Beijing Jiaotong University, Beijing100044, China
  • 3Beijing Special Machinery Research Institute, Beijing10014, China
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    DOI: 10.37188/OPE.20243206.0774 Cite this Article
    Yaodong WANG, Jinyang XU, Liqiang ZHU, Hongmei SHI, Yan FANG. Line feature coplanar constraint calibration method for lidar point cloud of tunnel contour[J]. Optics and Precision Engineering, 2024, 32(6): 774 Copy Citation Text show less

    Abstract

    In the measurement of subway tunnel profile parameters, it is necessary to calibrate the high-speed Lidar point cloud with high precision. In particular, the tunnel environment in large scenes has high requirements for calibration templates, complicated calibration process, and great influence on detection accuracy. To solve this problem, a novel calibration method for subway tunnel contour point cloud was proposed in this paper, and the algorithm was studied based on dual lidar measurement system. In this method, a special manual portable calibration system was designed. The objective function was established by using the calibration plate line features extracted from point cloud data, and the global optimal solution was found through the nonlinear optimization method combining genetic algorithm and Levenberg-Marquardt algorithm to realize the calibration of lidar. The experimental results show that the calibration error of the top rail is within ±1.5 mm. Static measurement accuracy X error within ±1 mm, Y error within ±4 mm; When the acquisition system performs data acquisition at a speed of 5 km/h, the dynamic measurement accuracy X error is within ±4 mm and Y error is within ±6 mm. This method can realize the high-precision calibration of lidar, the algorithm is robust, easy to operate, and has the characteristics of strong environmental adaptability.
    Yaodong WANG, Jinyang XU, Liqiang ZHU, Hongmei SHI, Yan FANG. Line feature coplanar constraint calibration method for lidar point cloud of tunnel contour[J]. Optics and Precision Engineering, 2024, 32(6): 774
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