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Efficient Algorithms for Automated Inspection of Freeform Surfaces

机译：自动检查自由曲面的高效算法

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摘要

This paper reports the development of efficient algorithms for automated inspection of freeform surfaces using point cloud data collected using an inspection system. The registration process to align the point cloud with the input CAD surface model is carried out in two phases, viz, rough registration followed by an accurate (fine) registration. For rough registration, algorithms based on the bounding box method and the convex hull method have been proposed. Fine registration is carried out using a computational geometry approach using a tessellated representation of the surface model. A random sampling technique has been integrated with the final registration algorithm to speed up the registration process. The algorithms have been compared with those reported in literature. Results show that the proposed algorithms substantially reduce the computational time, without sacrificing the accuracy of registration.
机译：本文报告了使用检查系统收集的点云数据来自动检查自由曲面的有效算法的发展。将点云与输入的CAD曲面模型对齐的配准过程分两个阶段进行，即粗略配准，然后进行精确（精细）配准。对于粗糙配准，提出了一种基于边界框法和凸壳法的算法。使用计算几何方法使用表面模型的细分表示法进行精细配准。随机采样技术已与最终注册算法集成在一起，以加快注册过程。该算法已与文献报道的算法进行了比较。结果表明，所提算法在不牺牲配准精度的前提下，大大减少了计算时间。

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