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Determining geometric error model parameters of a terrestrial laserscanner through Two-face Length-consistency and Networkmethods

机译:确定地面激光的几何误差模型参数双面长度一致性和网络扫描仪方法

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摘要

Terrestrial laser scanners (TLS) are increasingly used in large-scale manufacturing and assembly where required measurement uncertainties are on the order of few tenths of a millimeter or smaller. In order to meet these stringent requirements, systematic errors within a TLS are compensated in-situ through self-calibration. In the Network method of self-calibration, numerous targets distributed in the work-volume are measured from multiple locations with the TLS to determine parameters of the TLS error model. In this paper, we propose two new self-calibration methods, the Two-face method and the Length-consistency method. The Length-consistency method is proposed as a more efficient way of realizing the Network method where the length between any pair of targets from multiple TLS positions are compared to determine TLS model parameters. The Two-face method is a two-step process. In the first step, many model parameters are determined directly from the difference between front-face and back-face measurements of targets distributed in the work volume. In the second step, all remaining model parameters are determined through the Length-consistency method. We compare the Two-face method, the Length-consistency method, and the Network method in terms of the uncertainties in the model parameters, and demonstratethe validity of our techniques using a calibrated scale bar and front-faceback-face target measurements. The clear advantage of these self-calibrationmethods is that a reference instrument or calibrated artifacts are not required,thus significantly lowering the cost involved in the calibration process.
机译:陆地激光扫描仪(TLS)越来越多地用于大规模的制造和装配中,在这种情况下,所需的测量不确定度约为十分之几毫米或更小。为了满足这些严格的要求,TLS中的系统错误会通过自校准进行现场补偿。在网络自校准方法中,使用TLS从多个位置测量工作体积中分布的许多目标,以确定TLS误差模型的参数。在本文中,我们提出了两种新的自校准方法,即双面法和长度一致性法。长度一致性方法是实现网络方法的一种更有效的方法,在该方法中,对来自多个TLS位置的任意一对目标之间的长度进行比较以确定TLS模型参数。两面方法是一个两步过程。第一步,直接从分布在工作空间中的目标的正面和背面测量值之间的差异直接确定许多模型参数。第二步,通过“长度一致性”方法确定所有剩余的模型参数。我们在模型参数的不确定性方面比较了双面法,长度一致性法和网络法,并论证了校准的比例尺和正面对我们技术的有效性背面目标测量。这些自校准的明显优势方法是不需要参考仪器或校准的伪像,从而大大降低了校准过程中的成本。

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