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Method for registering lidar data in restrictive, tunnel-like environments.

机译:在限制性的,类似隧道的环境中注册激光雷达数据的方法。

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摘要

A new method of registering multiple range datasets collected in a GPS-denied, tunnel-like environment is presented. The method is designed to function with minimal user inputs and be effective over a wide range of changes in observation angle. The method is initially developed to operate on data in a general 2.5D coordinate system. Then, the general registration method is specifically tailored to a 2.5D spherical coordinate system. To apply the method, the range data is first filtered with a series of discrete Gaussian-based filters to construct a second-order Taylor series approximation to the surface about each sampled point. Finally, principal curvatures are calculated and compared across neighboring datasets to determine homologies and the best fit transfer matrix. The new method relaxes the minimum change in perspective requirement between neighboring datasets typical of other algorithms. Results from the application of the method on both synthetic and real-world data are shown. The real-world data comes from a series of high explosive tests performed in a tunnel environment. The tunnels were oriented horizontally in rock and constructed with boring equipment. The tunnel surfaces were surveyed with a Faro Focus3D terrestrial panorama scanning light detection and ranging (lidar) system both before and after a high explosive device was detonated inside the tunnel with the intent of documenting damage to the tunnel surface.
机译:提出了一种注册在GPS拒绝的,类似隧道的环境中收集的多个距离数据集的新方法。该方法旨在以最少的用户输入起作用,并且在观察角的宽范围变化中均有效。该方法最初被开发为对通用2.5D坐标系中的数据进行操作。然后,一般的套准方法专门针对2.5D球坐标系进行调整。为了应用该方法,首先使用一系列基于离散高斯的滤波器对距离数据进行滤波,以构造围绕每个采样点的表面的二阶泰勒级数逼近。最后,计算主曲率并在相邻数据集中进行比较,以确定同构关系和最佳拟合传递矩阵。新方法放宽了其他算法典型的相邻数据集之间的透视图要求的最小变化。显示了该方法在合成数据和实际数据上的应用结果。真实数据来自在隧道环境中进行的一系列高爆炸试验。隧道在岩石中水平定向,并配有钻孔设备。在隧道内部引爆高爆炸装置之前和之后,均使用Faro Focus3D地面全景扫描光检测和测距(激光)系统对隧道表面进行了调查,目的是记录在隧道表面造成的损坏。

著录项

  • 作者

    Zacherl, Walter D.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Remote sensing.;Optics.;Medical imaging.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 162 p.
  • 总页数 162
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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