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Aiming at self-calibration of terrestrial laser scanners using only one single object and one single scan

机译:旨在仅使用一个单一对象和一个单一扫描进行地面激光扫描仪的自校准

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摘要

When using terrestrial laser scanners for high quality analyses, calibrating the laser scanner is crucial due to unavoidable misconstruction of the instrument leading to systematic errors. Consequently, the development of calibration fields for laser scanner self-calibration is widespread in the literature. However, these calibration fields altogether suffer from the fact that the calibration parameters are estimated by analyzing the parameter differences of a limited number of substitute objects (targets or planes) scanned from different stations. This study investigates the potential of self-calibrating a laser scanner by scanning one single object with one single scan. This concept is new since it uses the deviation of each sampling point to the scanned object for calibration. Its applicability rests upon the integration of model knowledge that is used to parameterize the scanned object. Results show that this calibration approach is feasible leading to improved surface approximations. However, it makes great demands on the functional model of the calibration parameters, the stochastic model of the adjustment, the scanned object and the scanning geometry. Hence, to gain constant and physically interpretable calibration parameters, further improvement especially regarding functional and stochastic model is demanded.
机译:当使用地面激光扫描仪进行高质量分析时,由于不可避免地会造成仪器的错误构造而导致系统错误,因此校准激光扫描仪至关重要。因此,在文献中已经广泛开发了用于激光扫描仪自校准的校准场。然而,这些校准场完全受以下事实困扰:通过分析从不同站点扫描的有限数量的替代对象(目标或平面)的参数差异来估计校准参数。这项研究研究了通过一次扫描扫描一个物体来自动校准激光扫描仪的潜力。这个概念是新的,因为它使用每个采样点相对于扫描对象的偏差进行校准。它的适用性取决于用于参数化扫描对象的模型知识的集成。结果表明,这种校准方法可行,可以改善表面近似度。然而,这对校准参数的功能模型,调整的随机模型,被扫描物体和扫描几何形状有很高的要求。因此,为了获得恒定且可物理解释的校准参数,需要进一步的改进,尤其是关于功能和随机模型的改进。

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