约束改进的ICP点云配准方法

提高配准速度和精度是点云配准研究的重点。提出一种距离约束改进的迭代邻近点算法,针对邻近点法中找到的配准点,采用最近原则排除含相同点的点对;使用配准点重心作为参考点,结合点对距离约束排除误配准点对后进行点云配准;与使用点云重心作为参考点的方法和迭代邻近点算法进行了比较。实验结果表明,在配准速度和精度方面,提出的算法都有了提高,实现了点云的快速、准确配准。

ICP method improved by constraints for point cloud registration

To improve the speed and accuracy of point cloud registration is the research emphasis.An iteration close point algorithm improved by distance constraint is proposed.With the registration point found by using close point criterion,the nearest principle is used to remove the point pairs which have the same points.Since the center of registration point is regarded as a reference point,after the wrong point pairs are removed by using point pairs distance constraint,point cloud registration is carried out.This improved algorithm is compared with another method which regards the center of point cloud as a reference point and uses iteration close point principle.Experiment results show that the speed and accuracy of registration for the algorithm are improved.