Improved Strategy of Iterative Closest Point Algorithm

doi:10.3969/j.issn.1006-2475.2019.01.004

Abstract

Abstract: Iterative Closest Point (ICP) algorithm is the most common method of point cloud registration. Although its registration accuracy is high, the convergence speed is slow, and the registration effect of cloud with noise and low overlapping is not good. In view of this, three improved ICP algorithms are proposed in this paper. Aiming at the point cloud with noise, the probability ICP algorithm is used to suppress the influence of the noise points to the registration results and improve the registration accuracy. In order to improve the registration speed of the point cloud, the coordinate ICP algorithm is used to realize the rapid registration of the point cloud. Aiming at the low overlapping point clouds, the box ICP algorithm is used to improve the registration accuracy and speed. The registration experiment of rabbit point cloud shows that the three improved ICP algorithms have greatly improved the accuracy and speed of point cloud registration, and all are effective point cloud registration methods.

Key words: point cloud registration, iterative closest point, Gauss probability, coordinate axis, box structure

CLC Number:

TP391

(咸阳师范学院教育科学学院,陕西咸阳712000). Improved Strategy of Iterative Closest Point Algorithm[J]. Computer and Modernization, 2019, 0(01): 17-.

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