[1] Huang L, Chen S Y, Zhang J F, et al. Real-time motion tracking for indoor moving sphere objects with a LiDAR sensor[J]. Sensors, 2017, 17(9): 1932.

[2] DouillardB, UnderwoodJ, VlaskineV, et al. A pipeline for the segmentation and classification of 3D point clouds[M] ∥Khatib O, Kumar V, Sukhatme G. Experimental robotics. Berlin, Heidelberg: Springer, 2014: 585- 600.

[3] Lu XH, YaoJ, Tu JG, et al. Pairwise linkage for point cloud segmentation[J]. ISPRS Annals of Photogrammetry, RemoteSensing and Spatial InformationSciences, 2016, III-3: 201- 208.

[4] KlasingK, WollherrD, BussM. A clustering method for efficient segmentation of 3D laser data[C]∥2008 IEEE International Conference on Robotics and Automation, May 19-23, 2008, Pasadena, CA, USA. New York: IEEE, 2008: 4043- 4048.

[5] Luo Z, Habibi S, Mohrenschildt M. LiDAR based real time multiple vehicle detection and tracking[J]. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2016, 10(6): 1125-1132.

[6] 黄钢, 吴超仲, 吕能超, 等. 基于改进DBSCAN算法的激光雷达目标物检测方法[J]. 交通信息与安全, 2015, 33(3): 23-28.

    Huang G, Wu C Z, Lü N C, et al. A study of laser radar object detection based on improved DBSCAN algorithm[J]. Journal of Transport Information and Safety, 2015, 33(3): 23-28.

[7] Asvadi A, Premebida C, Peixoto P, et al. 3D Lidar-based static and moving obstacle detection in driving environments: an approach based on voxels and multi-region ground planes[J]. Robotics and Autonomous Systems, 2016, 83: 299-311.

[8] 杨飞, 朱株, 龚小谨, 等. 基于三维激光雷达的动态障碍实时检测与跟踪[J]. 浙江大学学报(工学版), 2012, 46(9): 1565-1571.

    Yang F, Zhu Z, Gong X J, et al. Real-time dynamic obstacle detection and tracking using 3D Lidar[J]. Journal of Zhejiang University(Engineering Science), 2012, 46(9): 1565-1571.

[9] 叶刚. 城市环境基于三维激光雷达的自动驾驶车辆多目标检测及跟踪算法研究[D]. 北京: 北京理工大学, 2016.

    YeG. Multi-target detection and tracking algorithm for autonomous driving car based on a 3D lidar in urban traffic environment[D]. Beijing: Beijing Institute of Technology, 2016.

[10] BörcsA, NagyB, BenedekC. Fast 3-D urban object detection on streaming point clouds[M] ∥Agapito L, Bronstein M, Rother C. Lecture notes in computer science. Cham: Springer, 2015, 8926: 628- 639.

[11] MoosmannF, PinkO, StillerC. Segmentation of 3D lidar data in non-flat urban environments using a local convexity criterion[C]∥2009 IEEE Intelligent Vehicles Symposium, June 3-5, 2009, Xi'an, China. New York: IEEE, 2009: 215- 220.

[12] 惠振阳, 程朋根, 官云兰, 等. 机载LiDAR点云滤波综述[J]. 激光与光电子学进展, 2018, 55(6): 060001.

    Hui Z Y, Cheng P G, Guan Y L, et al. Review on airborne LiDAR point cloud filtering[J]. Laser & Optoelectronics Progress, 2018, 55(6): 060001.

[13] Chu P, Cho S, Sim S, et al. A fast ground segmentation method for 3D point cloud[J]. Journal of Information Processing Systems, 2017, 13(3): 491-499.

[14] 黄作维, 刘峰, 胡光伟. 基于多尺度虚拟格网的LiDAR点云数据滤波改进方法[J]. 光学学报, 2017, 37(8): 0828004.

    Huang Z W, Liu F, Hu G W. Improved method for LiDAR point cloud data filtering based on hierarchical pseudo-grid[J]. Acta Optica Sinica, 2017, 37(8): 0828004.

[15] 王肖, 王建强, 李克强, 等. 智能车辆3-D点云快速分割方法[J]. 清华大学学报(自然科学版), 2014, 54(11): 1440-1446.

    Wang X, Wang J Q, Li K Q, et al. Fast segmentation of 3-D point clouds for intelligent vehicles[J]. Journal of Tsinghua University (Science and Technology), 2014, 54(11): 1440-1446.

[16] Bogoslavskyi I, Stachniss C. Efficient online segmentation for sparse 3D laser scans[J]. PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2017, 85(1): 41-52.

[17] 袁夏, 赵春霞. 一种应用于机器人导航的激光点云聚类算法[J]. 机器人, 2011, 33(1): 90-96.

    Yuan X, Zhao C X. A laser point cloud clustering algorithm for robot navigation[J]. Robot, 2011, 33(1): 90-96.

[18] MoosmannF. Interlacing self-localization, moving object tracking and mapping for 3D range sensors[M]. Germany: KIT Scientific Publishing, 2013.