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3D laser scanner calibration method based on invasive weed optimization and Levenberg-Marquardt algorithm

机译:基于侵入性杂草优化和Levenberg-Marquardt算法的3D激光扫描仪校准方法

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摘要

To estimate the measurement model parameters of a three-dimensional (3D) laser scanner, a spatial sphere-based calibration method by combining invasive weed optimization (IWO) and Levenberg-Marquardt (LM) algorithm is proposed in this paper. A nonlinear objective function of the 3D laser scanner calibration is established according to the distance constraint between each laser scanning point on a spherical calibration object and the center of the calibration sphere. To reduce the influence of measurement outliers, the Pseudo-Huber loss is also employed in the objective function. After that, a hybrid optimization algorithm combining IWO and LM is adopted to optimize the objective function, where the optimal model parameters of 3D laser scanner are sought. Thus, the model parameters calibration of the 3D laser scanner is realized. Experimental results demonstrate the high calibration accuracy and good consistency of model parameters of the proposed method. And the influences of the measurement noise and outliers can also be effectively suppressed.
机译:为了估计三维(3D)激光扫描仪的测量模型参数,本文提出了通过组合侵入性杂草优化(IWO)和Levenberg-Marquardt(LM)算法的空间球基校准方法。根据球面校准物体上的每个激光扫描点与校准球的中心之间的距离约束建立3D激光扫描仪校准的非线性物镜函数。为了减少测量异常值的影响,目的函数也采用伪HUBER损失。之后,采用组合IWO和LM的混合优化算法来优化目标函数,其中寻求3D激光扫描仪的最佳模型参数。因此,实现了3D激光扫描仪的模型参数校准。实验结果表明了所提出的方法的高校准精度和良好的一致性。也可以有效地抑制测量噪声和异常值的影响。

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