针对目前常用配准算法不能满足生产制造行业中高精度工艺要求的问题，本文基于三维点云提出一种改进三维形状上下文（3DSC）点云配准的有效解决方案。首先，通过改进的降采样方式设定阈值采集轮廓点云，对采集的点云依次进行三维网格划分形成形状上下文。然后，进行改进的3DSC初始配准，进而采用迭代最近点（ICP）精确配准，实现了源点云与目标点云之间的旋转平移变换。为验证改进算法的有效性，采用FPFH-ICP、PFH-ICP、传统3DSC和本文改进算法进行配准实验对比。实验结果表明，对于bunny点云和flowerpot点云，本文改进算法精度分别可达2.253 55e-05 m和9.969 02e-06 m，明显优于其他算法的配准精度。与传统3DSC配准算法相比，改进的3DSC配准算法可节省75%~85%的配准时间。改进的3DSC点云配准方法有利于提高配准精度且能优化配准时间，提高了配准效率。

In view of the problem that the commonly used registration algorithms cannot meet the high-precision process requirements in the manufacturing industry, this paper proposes an improved 3DSC point cloud registration based on the 3D point cloud. Firstly, the threshold value is set to collect the contour point cloud by the improved down-sampling method, and the collected point cloud is divided into 3D mesh in turn to form a 3D shape context. Then, the improved 3DSC coarse registration is performed, and the ICP fine registration is used to realize the rotation and translation transformation between the source point cloud and the target point cloud. In order to verify the effectiveness of the improved algorithm, the traditional 3DSC, FPFH-ICP, PFH-ICP and the improved algorithm in this paper are used to compare the registration experiments. The experiment results show that the accuracy of the improved algorithm can reach 2.253 55e-05 m and 9.969 02e-06 m respectively for the bunny point cloud and the flowerpot point cloud, which is obviously better than the registration accuracy of other algorithms. Compared with the traditional 3DSC registration algorithm, the improved 3DSC registration algorithm can save 75%~85% of the registration time. The improved 3DSC point cloud registration method is beneficial to improve the registration accuracy, optimize the registration time, and improve the registration efficiency.