• Electronics Optics & Control
  • Vol. 26, Issue 3, 59 (2019)
LI Chuan-long, DIAN Song-yi, and LIU Hai-liang
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2019.03.013 Cite this Article
    LI Chuan-long, DIAN Song-yi, LIU Hai-liang. Point Cloud Registration Based on Improved Dynamic Differential Evolution Algorithm[J]. Electronics Optics & Control, 2019, 26(3): 59 Copy Citation Text show less

    Abstract

    Aiming at the problem of point cloud registration under different angles of view, a registration method based on the Improved Dynamic Differential Evolution(IDDE) algorithm is proposed.Firstly, Principal Component Analysis(PCA) is used to estimate the curvature and normal vector of the point cloud, and the average angle between the normal vectors of each point and its k-nearest neighbors is calculated.Subsequently, the first feature point extraction is conducted by the first feature parameter constructed by the curvature and the average normal vector angle, and the second feature point extraction is conducted by the second feature parameter constructed by curvature.Finally, according to the acquired feature point cloud, the registration parameter is calculated by the IDDE algorithm based on the coupled-optimal ordering mutation proposed in this paper, thus the initial registration result can be obtained, and the fine registration is achieved by an improved iterative closest point algorithm.Experiment shows that the proposed registration algorithm has the advantages of short registration time and high registration accuracy.
    LI Chuan-long, DIAN Song-yi, LIU Hai-liang. Point Cloud Registration Based on Improved Dynamic Differential Evolution Algorithm[J]. Electronics Optics & Control, 2019, 26(3): 59
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