• Laser & Optoelectronics Progress
  • Vol. 57, Issue 20, 201105 (2020)
Chang Liu, Jin Zhao*, Zihao Liu, Xiqiao Wang, and Kuncheng Lai
Author Affiliations
  • School of Mechanical Engineering, GuiZhou University, GuiYang, GuiZhou 550025, China
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    DOI: 10.3788/LOP57.201105 Cite this Article Set citation alerts
    Chang Liu, Jin Zhao, Zihao Liu, Xiqiao Wang, Kuncheng Lai. Improved Lidar Obstacle Detection Method Based on Euclidean Clustering[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201105 Copy Citation Text show less
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    [6] Tarsha-Kurdi F, Landes T, Grussenmeyer P[2020-01-02]. Hough-transform and extended RANSAC algorithms for automatic detection of 3D building roof planes from lidar data [2020-01-02].https:∥hal.ird.fr/AO-ARCHITECTURE/halshs-00264843v1..

    [7] Yu G, Grossberg M D, Wolberg G et al. Think globally, cluster locally: a unified framework for range segementation. [C]∥Fourth International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT), June 18-20, 2008, Atlanta, GA, USA. [S.l.: s.n.](2008).

    [8] Xue L J, Qi C K, Zhang B et al. Object size and orientation recognition based on 3D point cloud Euclideam clustering and RANSAC boundary fitting[J]. Machine Design and Research, 34, 44-48,53(2018).

    [9] Liu R S. Research on multi-feature fusion recognition algorithm based on minimum Euclidean distance between samples[J]. Computer & Digital Engineering, 45, 2373-2378(2017).

    [10] Chen G B, Gao Z H, He L. Step-by-step automatic calibration algorithm for exterior parameters of 3D lidar mounted on vehicle[J]. Chinese Journal of Lasers, 44, 1010004(2017).

    Chang Liu, Jin Zhao, Zihao Liu, Xiqiao Wang, Kuncheng Lai. Improved Lidar Obstacle Detection Method Based on Euclidean Clustering[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201105
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