基于SAC-IA和NDT融合的点云配准方法

提出一种基于采样一致性初始配准（SAC-IA）和正态分布变换（NDT）配准融合的点云配准方法。首先计算出待配准点云和目标点云的快速点特征直方图(FPFH）特征；然后依据该特征，利用SAC-IA算法求出初始转换矩阵，完成初始配准；最后在初始配准的基础上，利用NDT算法对两片点云进行精配准。实验结果表明，该方法的配准精度显著优越于ICP算法，且配准效率也有所提升。

Point Cloud Registration Method Based on SAC-IA and NDT Fusion

We propose a point cloud registration method based on the fusion of sample consensus initial alignment(SAC-IA)and normal distribution transformation(NDT)registration.First,we calculate the fast point feature histogram(FPFH)feature of the point cloud to be registered and the target point cloud;second,according to the feature of two pieces of point cloud and using the SAC-IA algorithm to find the initial transformation matrix,thereby completing the initial registration;finally,on the basis of the initial registration,we use the NDT algorithm to precisely register the two point clouds.Experimental results show that the registration accuracy of this method is significantly superior to the ICP algorithm,and the registration efficiency is also relatively improved.