APPLIED LASER, Volume. 42, Issue 10, 126(2022)

Detection Method and Experiment of the Cone Based on Improved Euclidean Clustering

Huang Ruiqin1, Liang Hongbo2, Li Qiang1, Yang Aixi3, and Zhang Xinwen1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(3)

    [2] [2] KABZAN J, VALLS M I, REIJGWART V J F, et al. AMZ Driverless: The full autonomous racing system[J]. Journal of Field Robotics, 2020,37(7):1267-1294.

    [6] [6] ZERMAS D, IZZAT I, PAPANIKOLOPOULOS N. Fast segmentation of 3D point clouds: a paradigm on LiDAR data for autonomous vehicle applications[C]//2017 IEEE International Conference on Robotics and Automation. Singapore: IEEE, 5067-5073.

    [10] [10] TORR P H S, ZISSERMAN A. MLESAC: A new robust estimator with application to estimating image geometry[J]. Computer Vision and Image Understanding, 2000, 78(1): 138-156.

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    Huang Ruiqin, Liang Hongbo, Li Qiang, Yang Aixi, Zhang Xinwen. Detection Method and Experiment of the Cone Based on Improved Euclidean Clustering[J]. APPLIED LASER, 2022, 42(10): 126

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    Paper Information

    Received: Jun. 15, 2022

    Accepted: --

    Published Online: May. 23, 2024

    The Author Email:

    DOI:10.14128/j.cnki.al.20224210.126

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