摘要

Registration of point clouds is vital in point cloud data processing. By registering, the point cloud data from different views are transformed into a common coordinate system. In the iterative closest projected point (ICPP) method, the three nearest points are used to form a patch or plane and the performance is greatly affected by noise. More points may be used to construct a plane to reduce the effect of noise, but such a technique may not be suited for the scenarios where the physical surface is not a 2-D pane but a curved surface. In this paper, the iterative closest optimal plane (ICOPlane) method is developed. We propose a method of searching the optimal plane over a possible curved surface for registration of point clouds. In addition, in order to consider the errors of all variables, a constrained weighted total least squares algorithm is derived to estimate the plane parameters and transformation parameters. Both simulated and real experiments are carried out to examine the performance of the developed method, and experimental results demonstrate that the developed method can produce more accurate transformation parameters in comparison with the ICPP method.