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首页> 外文会议>International Conference on Measuring Technology and Mechatronics Automation >An Allowance Optimal Distribution Method Based on Improved Iterative Closest Point Algorithm
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An Allowance Optimal Distribution Method Based on Improved Iterative Closest Point Algorithm

机译：一种基于改进迭代最近点算法的津贴优化分布方法

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摘要

To deal with the problem about allowance optimal distribution, a method based on improved iterative closest point algorithm was put forward. The method consists of the following parts. Firstly, Measure the blank using a 3D laser scanner. And then apply the improved iterative algorithm to the measured model and the ideal CAD model to optimize the allocation distribution. In the improved algorithm, a coarse registration based on the principal component analysis algorithm was carried out to improve the speed and accuracy of the fine registration. And the iterative closet point algorithm was applied for the fine registration, where a KD-Tree topology of point cloud data was established to improve the speed of searching the nearest point. At the end of the paper, an example has been developed with the window feature of a cabin to verify the improved algorithm. The results show the proposed method is effective and feasible.
机译：要处理津贴最佳分布的问题，提出了一种基于改进的迭代最接近点算法的方法。该方法包括以下部分。首先，使用3D激光扫描仪测量空白。然后将改进的迭代算法应用于测量模型和理想的CAD模型，以优化分配分布。在改进的算法中，基于主成分分析算法的粗略配准，以提高精细配准的速度和精度。并且迭代壁橱点算法应用于精细注册，其中建立了点云数据的KD树拓扑，以提高搜索最接近点的速度。在论文的末尾，已经使用驾驶室的窗口特征开发了一个示例，以验证改进的算法。结果表明所提出的方法是有效和可行的。

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