Journal of System Simulation
Abstract
Abstract: Accurate estimation of berthing parameters is a prerequisite for unmanned surface vessel autonomous berthing. A method for berthing parameter estimation is proposed based on shipborne 3D LiDAR. The method consists of two main modules: ship pose estimation and berthing state estimation. In the berthing position estimation module, raw point cloud data undergoes preprocessing algorithms aims at downsampling and removing outliers. Point cloud registration algorithms are employed to determine the vessel's position during the berthing process. The berthing state estimation module extracts berth boundary information by using the MSAC algorithm, and on the basis of this information, calculates the berthing parameters. Experimental analysis results show that the ship pose information and berthing parameter information obtained by the algorithm are consistent with reality. The average berthing distance error is less than 0.023 m, and the average angle error is less than 0.26° , which verifies the accuracy and rationality of this berthing parameter estimation algorithm.
Recommended Citation
Wang, Haichao; Yin, Yong; Jing, Qianfeng; and Cong, Lin
(2024)
"Estimation of the Berthing Parameter of Unmanned Surface Vessels Based on 3D LiDAR,"
Journal of System Simulation: Vol. 36:
Iss.
8, Article 1.
DOI: 10.16182/j.issn1004731x.joss.24-0262
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss8/1
First Page
1737
Last Page
1748
CLC
U675.6+2; TP391
Recommended Citation
Wang Haichao, Yin Yong, Jing Qianfeng, et al. Estimation of the Berthing Parameter of Unmanned Surface Vessels Based on 3D LiDAR[J]. Journal of System Simulation, 2024, 36(8): 1737-1748.
DOI
10.16182/j.issn1004731x.joss.24-0262
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