HIGH ACCURATE POINTWISE (GEO-)REFERENCING OF A K-TLS BASED MULTI-SENSOR-SYSTEM
HIGH ACCURATE POINTWISE (GEO-)REFERENCING OF A K-TLS BASED MULTI-SENSOR-SYSTEM
复制标题
基于 K-TLS 的多传感器系统的高精度逐点（地理）参考
DOI：
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发表时间：
2018
期刊：
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通讯作者：
I. Neumann
中科院分区：
文献类型：
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作者：
J. Hartmann;P. Trusheim;H. Alkhatib;J. Paffenholz;D. Diener;I. Neumann
抽象。近年来，工业生产中的要求，例如，无论是飞机还是船只，都在增加。除了标准偏差为1 mm的高精度要求外，还需要高效的3D对象捕获。在效率方面，近年来，动态激光扫描（k-TLS）已被证明其价值。它可以被视为成熟的静态地面激光扫描（s-TLS）的替代方案。然而，目前基于k-TLS的多传感器系统（MSS）无法满足高精度要求。因此，必须开发新的基于k-TLS的MSS和合适的处理算法。在这篇文章中，将提出一种新的基于k-TLS的MSS。主要重点将放在（地理）参照过程上。由于高精度的要求，一个新的外部（地理）参考程序在这里使用。因此，配备有轮廓激光扫描仪的移动的平台将由激光跟踪仪跟踪。由于激光扫描仪的测量频率明显高于激光跟踪仪的测量频率，直接逐点（地理）参考是不可能的。为了实现这一点，卡尔曼滤波器模型的建立和实施。在预测步骤中，根据所确定的平台速度来移动每个点。由于平台的非线性运动的迭代扩展卡尔曼滤波（iEKF）在这里使用。此外，与k-TLS为基础的MSS和与s-TLS的面板进行了测试测量。为了比较结果，使用M3 C2算法估计s-TLS 3D点云和k-TLS 3D点云之间的3D距离。可以注意到，使用系统模型进行（地理）参考是必不可少的。结果表明，该系统达到了高精度要求。
Abstract. In recent years, the requirements in the industrial production, e.g., ships or planes, have been increased. In addition to high accuracy requirements with a standard deviation of 1 mm, an efficient 3D object capturing is required. In terms of efficiency, kinematic laser scanning (k-TLS) has been proven its worth in recent years. It can be seen as an alternative to the well established static terrestrial laser scanning (s-TLS). However, current k-TLS based multi-sensor-systems (MSS) are not able to fulfil the high accuracy requirements. Thus, a new k-TLS based MSS and suitable processing algorithms have to be developed. In this contribution a new k-TLS based MSS will be presented. The main focus will lie on the (geo-)referencing process. Due to the high accuracy requirements, a novel procedure of external (geo-)referencing is used here. Hereby, a mobile platform, which is equipped with a profile laser scanner, will be tracked by a laser tracker. Due to the fact that the measurement frequency of the laser scanner is significantly higher than the measurement frequency of the laser tracker a direct point wise (geo-)referencing is not possible. To enable this a Kalman filter model is set up and implemented. In the prediction step each point is shifted according to the determined velocity of the platform. Because of the nonlinear motion of the platform an iterative extended Kalman filter (iEKF) is used here. Furthermore, test measurements of a panel with the k-TLS based MSS and with s-TLS were carried out. To compare the results, the 3D distances with the M3C2-algorithm between the s-TLS 3D point cloud and the k-TLS 3D point cloud are estimated. It can be noted, that the usage of a system model for the (geo-)referencing is essential. The results show that the mentioned high accuracy requirements have been achieved.