• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>SPIE Conference on Automated Visual Inspection and Machine Vision >An Advanced Method for Matching Partial 3D Point Clouds to Free-Form CAD Models for In-situ Inspection and Repair
【24h】

An Advanced Method for Matching Partial 3D Point Clouds to Free-Form CAD Models for In-situ Inspection and Repair

机译：一种高级方法，将部分3D点云匹配到自由形式CAD模型，用于原位检测和修复

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

3D scanning is a key process in the fields of robotics and computer vision, and can be used for shape comparison between real-world features and Computer-Aided Design (CAD) models. In order to be beneficial, algorithms must be able to accurately register the 3D point cloud to the model surface. In this paper, we propose a registration method using Correlation Coefficients of the point cloud dimensions along with pose calculated by Procrustes Analysis to provide an ideal global registration for the Iterative Closest Point (ICP) algorithm. The method is analysed in the context of objects that are largely smooth and featureless, with only partial scans captured of the objects' surfaces, and improves the accuracy of registration in such scenarios. This work has resulted in registrations with more accuracy in cases where a rotational alignment is known but a specific position cannot be identified, than if either ICP or Procrustes are used individually, or when Procrustes is used to provide an initial transformation to ICP. It is shown that by applying the proposed method to partially scanned objects, the Root Mean Square Error (RMSE) is significantly reduced. The method is compared with the SAC-IA alignment algorithm, implemented in the Point Cloud Library (PCL), and the results show 0.4mm RMSE for the proposed method and 24.5mm RMSE for the SAC-IA with ICP. The findings in this work could be used in industrial applications including in-situ robotic repair and inspection of free-form manufactured parts.
机译：3D扫描是机器人和计算机视野领域的一个关键过程，可用于现实世界特征和计算机辅助设计（CAD）型号之间的形状比较。为了有益，算法必须能够准确地将3D点云注册到模型表面。在本文中，我们提出了一种使用Point云尺寸的相关系数以及由PROCRUSTES分析计算的姿势来提出一个注册方法，为迭代最近点（ICP）算法提供理想的全球注册。该方法在基本上是平滑且非特性的对象的上下文中分析了该方法，只有对象表面捕获的部分扫描，并提高了这种情况的登记的准确性。在旋转对准是已知的但不能识别特定位置的情况下，该工作导致了更准确的注册，而不是单独使用ICP或PROCRUSTES，或者当使用初始转换为ICP提供初始转换时，或者当使用初始位置。结果表明，通过将所提出的方法应用于部分扫描对象，根均方误差（RMSE）显着降低。将该方法与SAC-IA对准算法进行比较，在点云库（PCL）中实现，结果显示了所提出的方法0.4mm RMSE，具有ICP的SAC-IA的24.5mm RMSE。这项工作中的调查结果可用于工业应用，包括原位机器人修复和自由式制造零件的检查。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号