Ship Identification Algorithm Based on 3D Point Cloud for Automated Ship Loaders

• Published in: Journal of coastal research Vol. 73; no. sp1; pp. 28 - 34
• Main Authors: Mi, Chao, Shen, Yang, Mi, Weijian, Huang, Youfang
• Format: Journal Article
• Language: English
• Published: Coastal Education and Research Foundation 01.12.2015; Coastal Education & Research Foundation (CERF)
• Subjects: Algorithms; Automated ship loader; Automatic control; automation; bulk terminal; Cargo holds; Container terminals; crane; Experimental results; Lasers; LiDAR; Marine and Coastal Environment; point cloud; Radar; Sensors; Ships; target identification
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/SI73-006.1

Mi, C.; Shen, Y.; Mi, W., and Huang, Y., 2015. Ship identification algorithm based on 3D point cloud for automated ship loader. With the development of bulk port automation, the ship loader as the main quayside machine of bulk terminal is required for transformation from manual operation to automation. The ship identification method is a key inspection technique for automated ship loaders. In this paper, a fast ship identification algorithm was formulated based on the 3D point cloud of the ship, as generated by the Laser Measurement Systems (LMS) mounted on the ship loader. To meet the requirement of real-time computing for the automated ship loader, the 3D point cloud was first processed to reduce its dimensions from 3D point cloud into a 2D image. A projection method was then applied to locate and identify all bulk cargo holds in the ship. Finally, a group of experiments on ship identification was conducted using this algorithm in the Coal Terminal of Tianjin Port. The results showed that the computing time for a whole ship was lower than 200 ms and the error of the algorithm was lower than 10%, meeting the requirement of automated ship loaders.