激光雷达具有测距精度高、全天候工作、抗干扰能力强等优点。随着交通自动化、智能化的发展趋势，对于激光雷达的研究越来越丰富，但在水上交通领域上的应用研究相对较少。本文总结了船舶靠泊的多种方式及激光雷达的不同特点；指出激光雷达目前在靠泊领域应用中仍存在的问题；探讨了岸基激光雷达辅助系统在船舶靠泊的态势感知以及船载激光雷达在无人船领域靠泊中的应用；描述了激光雷达点云的数据处理过程，通过点云数据的获取，构建智慧船舶靠泊系统，结果可为智慧船舶靠泊的推广应用提供技术参考。
LIDAR has the advantages of high ranging accuracy, all-weather operation and strong anti-interference ability. With the trend of traffic automation and intelligence, the research on LiDAR is getting richer and richer, but the application research in the field of waterborne traffic is rather limited. This paper summarizes the various ways of ship berthing and the application of different features of LiDAR; points out the problems that still exist in the application of LiDAR in the field of berthing; and discusses the application of shore-based LiDAR auxiliary system in the situational awareness of ship berthing as well as the application of ship-mounted LiDAR in the unmanned ship field of berthing. The data processing process of LiDAR point cloud is described, and the intelligent ship berthing system is constructed through the acquisition of point cloud data. The results can provide technical reference for the promotion and application of intelligent ship berthing.
2025,47(7): 1-5 收稿日期：2024-5-15
DOI：10.3404/j.issn.1672-7649.2025.07.001
分类号：U675
基金项目：国家重点研发计划资助项目（2023YFB4302300）；中央高校基本科研业务费专项资金资助项目（3132023507）；大连市高层次人才团队创新支持计划资助项目（2022RG02）
作者简介：包博文(2000-),男,硕士研究生,研究方向为激光雷达靠泊
参考文献：
[1] 2014年度交通运输安全生产事故报告(水上交通领域)[J]. 中国海事, 2015, (6): 32.
[2] 闫晓飞. 基于三维激光点云数据的船舶靠泊监测技术[D]. 大连: 大连海事大学, 2017.
[3] 兰加芬, 郑茂, 初秀民, 等. 基于激光雷达的船舶位姿感知方法研究[J/OL]. 武汉大学学报(信息科学版), 2023: 1-11.
[4] 马守军. 基于岸基激光雷达的靠泊船舶辅助信息的获取研究[J]. 珠江水运, 2023(14): 77-79.
MA S J. Acquisition of auxiliary information of berthing ships based on shore-based LiDAR[J]. Pearl River Delta (PRD) Water Transport, 2023(14): 77-79.
[5] LEE H T, LEE J S, SON W J, et al. Development of machine learning strategy for predicting the risk range of ship's berthing velocity [J]. Journal of Marine Science and Engineering, 2020, 8(5): 49112.
[6] 胡斌. 基于激光雷达的无人船靠泊信息感知研究[D]. 大连: 大连海事大学, 2022.
[7] 蒲文浩, 刘锡祥, 陈昊, 等. 多传感器融合的激光雷达点云矫正与定位方法[J]. 激光与光电子学进展, 2023, 60(24): 275-282.
PU W H, LIU X X, CHEN H. LiDAR point cloud correction and location based on multisensor fusion[J]. Laser & Optoelectronics Progress, 2023, 60(24): 275-282.
[8] 李鹏江. 基于核点卷积的三维点云语义分割算法研究[D]. 燕山: 燕山大学, 2023.
[9] 宋振杰. 基于图神经网络的三维点云分类分割算法研究[D]. 镇江: 江苏科技大学, 2023.
[10] 汪争锐, 郭芃, 冯立辉. 基于局部空间信息表征融合和信息深度残差提取的点云分类分割算法[J]. 自动化与仪器仪表, 2023(5): 1-5+9.
WANG Z R, GUO P, FENG L H. Point cloud classification and segmentation algorithm based on local information representing and fusing and information deep residual extractor[J]. Automation & Instrumentation, 2023(5): 1-5+9.
[11] 张蕊, 李广云, 李明磊, 等. 利用PCA-BP算法进行激光点云分类方法研究[J]. 测绘通报, 2014(7): 23-26.
[12] 龚亮. 机载LiDAR点云数据分类技术研究[D]. 郑州: 解放军信息工程大学, 2011.
[13] WANG H, YIN Y, JING Q, et al. Berthing assistance system for autonomous surface vehicles based on 3D LiDAR [J]. Ocean Engineering, 2024, 291.
[14] 韩金霞, 孙正伟. 激光雷达和单目视觉船舶智能导航系统[J]. 舰船科学技术, 2023, 45(5): 140-143.
HAN J X, SUN Z W. Ship intelligent navigation system based on lidar and monocular vision[J]. Ship Science and Technology, 2023, 45(5): 140-143.
[15] 王卓琳. 船舶靠泊过程中激光雷达与毫米波雷达的数据融合[D]. 大连: 大连海事大学, 2023.
[16] 陈静. 基于视觉与激光雷达融合的无人船靠泊环境感知系统研究[D]. 武汉: 武汉理工大学, 2022.
[17] WANG H, YIN Y, JING Q. Comparative analysis of 3D LiDAR scan-matching methods for state estimation of autonomous surface vessel [J]. Journal of Marine Science and Engineering, 2023, 11(4):77-91.
[18] 郭珏菡, 柳晨光, 于周讯, 等. 智能船舶激光雷达感知技术综述与展望[C]//中国智能交通协会. 第十五届中国智能交通年会科技论文集(1), 中国工信出版集团, 2020.
[19] CHEN C, LI Y. Ship berthing information extraction system using three-dimensional light detection and ranging data [J]. Journal of Marine Science and Engineering, 2021, 9(7): 74-81.
[20] WANG T Q, LI Y, CHEN C. Spatial state analysis of ship during berthing and unberthing process based on 3D LiDAR [J]. Ocean Engineering, 2023, 28(8): 241-255.
[21] 中国船级社. 智能船舶规范(2015)[EB/OL]. (2019-01-15)[2024-05-07]. https://www.ccs.org.cn/ccswz/specialDetail?id=201900001000006099
[22] 穆胜军, 汪伟奎, 张华, 等. 船舶智能辅助靠泊系统研究与开发[J]. 珠江水运, 2021(22): 111-112.
MU S J, WANG W K, ZHANG H, et al. Research and development of intelligent auxiliary berthing system for ships[J]. Pearl River Delta (PRD) Water Transport, 2021(22): 111-112.
