Unmanned surface vehicle berthing technology based on multi-sensor fusion SLAM 

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  • (1a. Marine Engineering College; 1b. Marine Electrical Engineering College, Dalian Maritime University, Dalian 116026, China; 2. Ganjingzi Marine Department, Dalian Maritime Safety Administration, Dalian 116000, China)

Received date: 2023-06-04

  Revised date: 2023-09-20

  Accepted date: 2023-09-20

  Online published: 2023-09-20

Abstract

Aiming at the application requirements of autonomous berthing of unmanned surface vehicles(USV) in harbor areas, the autonomous berthing technology of USV based on multi-sensor fusion of simultaneous localization and mapping(SLAM) was proposed from the perspective of enhancing environmental perception accuracy and location ability. In order to solve the problems of poor timeliness and incomplete environmental representation caused by the dynamic changes in navigable areas, an integrated accurate sensing scheme of water-underwater was proposed to obtain passable information. Aiming at the problem of large satellite positioning deviation and difficult to obtain attitude information, the depth information sensed by USV in real time was matched with the prior point cloud map to obtain accurate position and attitude information. Considering the demand for specific attitude of the USV during berthing, the USV motion model and collision avoidance model were established, and the motion performance parameters of the USV were obtained by using ship manipulation tests,and took it as the constraints of the Reeds-Shepp optimization curve to eliminate the sharp inflection points on the trajectory. According to the real data, the USV model, sensor model and port environment model were constructed for autonomous navigation berthing simulation experiments, and results show that the proposed autonomous berthing technology of USV based on multi-sensor fusion SLAM can complete accurately harbor berthing task.

Cite this article

JIA Wei, WANG Ning, ZHANG Fuyu, ZHANG Xuefeng, LI Jielong, WU Haojun, SUN Henan . Unmanned surface vehicle berthing technology based on multi-sensor fusion SLAM [J]. Journal of Dalian Maritime University, 2023 , 49(4) : 65 -75 . DOI: 10.16411/j.cnki.issn1006-7736.2023.04.008

References

[1]WANG S J. Brave to do intelligent ship no man's land pathfinder[J]. China Ship Survey, 2020, 237(2): 20-23.
[2]鲁德伟,韩晓宝,牛志斌.无人船在港口水域海事监管中的应用探讨[J],中国海事, 2020, 174(1): 43-45.
LU D W, HAN X B, NIU Z B. Discussion on the application of unmanned vessel on maritime supervision within port sea area[J]. China Maritime Safety, 2020, 174(1): 43-45. (in Chinese) 
[3]HAN J, CHO Y, KIM J, et al. Autonomous collision detection and avoidance for ARAGON USV: Development and field tests[J]. Journal of Field Robotics, 2020, 37(6): 987-1002.
[4]张英俊, 翟鹏宇. 海运船舶自主避碰技术研究进展与趋势[J]. 大连海事大学学报, 2022, 48(3):1-11.
ZHANG Y J, CUI P Y. An autonomous obstacle avoidance method for unmanned vehicles facing unstable obstacles[J]. Journal of Dalian Maritime University, 2022,48(3):1-11.(in Chinese)
[5]LIU J, ZHAN J, GUO C, et al. Data logic structure and key technologies on intelligent high-precision map[J]. Journal of Geodesy and Geoinformation Science, 2020,3(3):1.
[6]SANKALPRAJAN P, MUPPIDI A J, PAGALA P S. Analysis of Computational Need of 2D-SLAM Algorithms for Unmanned Ground Vehicle[C]//2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2020: 230-235.
[7]WANG W, SHAN T, LEONI P, et al. Roboat II: A novel autonomous surface vessel for urban environments[C]//2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE,2020: 1740-1747.
[8]CHENG Y, JIANG M, ZHU J, et al. Are we ready for unmanned surface vehicles in inland waterways? The usvinland multisensor dataset and benchmark[J]. IEEE Robotics and Automation Letters,2021,6(2):3964-3970.
[9]ZHOU B, HE Y, QIAN K, et al. S4-SLAM: A real-time 3D LIDAR SLAM system for ground/watersurface multi-scene outdoor applications[J]. Autonomous Robots, 2021,45:77-98.
[10]包涛, 周则兴, 陈卓, 等. 面向不稳定障碍物的无人艇自主避障方法[J]. 大连海事大学学报,47(3):8-15.
BAO T, ZHOU Z X, CHEN Z, et al. An autonomous obstacle avoidance method for unmanned vehicles facing unstable obstacles[J]. Journal of Dalian Maritime University,47(3):8-15.(in Chinese)
[11]崔金龙, 李元奎, 索基源, 等. 基于改进 A* 算法的船舶航向航速协同优化方法[J]. 大连海事大学学报,48(4):29-37.
CUI J L, LI Y K, SUO J Y, et al. Ship heading speed co-optimization method based on improved A* algorithm[J]. Journal of Dalian Maritime University,48(4):29-37.(in Chinese)
[12]LIAO Y, JIA Z, ZHANG W, et al. Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis[J]. Applied Ocean Research,2019,86:47-60.  
[13]SUYAMA R, MIYAUCHI Y, MAKI A. Ship trajectory planning method for reproducing human operation at ports[J]. Ocean Engineering,2022,266:112763.
[14]SHI Y, WANG P, WANG X. An Autonomous Valet Parking Algorithm for Path Planning and Tracking[C]//2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE,2022:1-7.

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