Laser & Optoelectronics Progress, Volume. 62, Issue 6, 0615010(2025)

Point Cloud Registration Based on Surface Feature Degree and Improved Dung Beetle Optimization Algorithm

Junchao Zhu*, Siyuan Song, Fangfang Han, and Minghui Zhang
Author Affiliations
  • School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China
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    References(22)

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    [13] Zhao M F, Huang Z, Song T et al. Point cloud registration method based on sample consensus initial alignment and iterative closest point algorithm[J]. Laser Journal, 40, 45-50(2019).

    [15] Li Y H, Yan J G, Wang X Y. Lidar target point cloud alignment based on improved neighborhood curvature with iteration closest point algorithm[J]. Laser & Optoelectronics Progress, 60, 0228008(2023).

    [19] Zhen R, Yuan M M, Wu X J et al. Unmanned aerial vehicle flight path planning based on improved dung beetle algorithm[J]. Radio Engineering, 54, 2412-2424(2024).

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    [22] Yuan Z D. Research on the optimal scheduling of pumping stations based on chaotic artificial electric field algorithm[D](2023).

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    Junchao Zhu, Siyuan Song, Fangfang Han, Minghui Zhang. Point Cloud Registration Based on Surface Feature Degree and Improved Dung Beetle Optimization Algorithm[J]. Laser & Optoelectronics Progress, 2025, 62(6): 0615010

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    Paper Information

    Category: Machine Vision

    Received: Jul. 9, 2024

    Accepted: Sep. 3, 2024

    Published Online: Mar. 18, 2025

    The Author Email:

    DOI:10.3788/LOP241656

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