Chen Xuzhan, Chen Youping, Chen Bing, He Zhuo, Ma Yunxiu, Zhang Dailin, Najjaran Homayoun
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
School of Material Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel). 2021 Jan 14;21(2):559. doi: 10.3390/s21020559.
Laser triangulation sensors (LTS) are widely used to acquire depth information in industrial applications. However, the parameters of the components, e.g., the camera, of the off-the-shelf LTS are typically unknown. This makes it difficult to recalibrate the degenerated LTS devices during regular maintenance operations. In this paper, a novel one-dimensional target-based camera intrinsic matrix-free LTS calibration method is proposed. In contrast to conventional methods that calibrate the LTS based on the precise camera intrinsic matrix, we formulate the LTS calibration as an optimization problem taking all parameters of the LTS into account, simultaneously. In this way, many pairs of the camera intrinsic matrix and the equation of the laser plane can be solved and different pairs of parameters are equivalent for displacement measurement. A closed-form solution of the position of the one-dimensional target is proposed to make the parameters of the LTS optimizable. The results of simulations and experiments show that the proposed method can calibrate the LTS without knowing the camera intrinsic matrix. In addition, the proposed approach significantly improves the displacement measurement precision of the LTS after calibration. In conclusion, the proposed method proved that the precise camera intrinsic matrix is not the necessary condition for LTS displacement measurement.
激光三角测量传感器（LTS）在工业应用中被广泛用于获取深度信息。然而，现成的LTS的组件参数，例如相机参数，通常是未知的。这使得在定期维护操作期间重新校准退化的LTS设备变得困难。本文提出了一种基于一维目标的新型无相机内参矩阵的LTS校准方法。与基于精确相机内参矩阵校准LTS的传统方法不同，我们将LTS校准表述为一个优化问题，同时考虑LTS的所有参数。通过这种方式，可以求解多对相机内参矩阵和激光平面方程，并且不同的参数对在位移测量方面是等效的。提出了一维目标位置的闭式解以使LTS的参数可优化。仿真和实验结果表明，所提出的方法可以在不知道相机内参矩阵的情况下校准LTS。此外，所提出的方法在校准后显著提高了LTS的位移测量精度。总之，所提出的方法证明了精确的相机内参矩阵不是LTS位移测量的必要条件。
