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Achieving port automation of machinery at bulk terminals is a challenging problem due to the volatile operation environments and complexity of bulk loading compared to the situations in container terminals. In order to facilitate port automation, we present a method of hull modeling (reconstruction of hull’s structure) and operation target (cargo holds under loading) identification based on 3D point cloud collected by Laser Measurement System mounted on the ship loader. In the hull modeling algorithm, we incrementally register pairs of point clouds and reconstruct the 3D structure of bulk ship’s hull blocks in details through process of encoder data of the loader, FPFH feature matching and ICP algorithm. In the identification algorithm, we project real-time point clouds of the operation zone to spherical coordinate and transforms the 3D point clouds to 2D images for fast and reliable identification of operation target. Our method detects and complements four edges of the operation target through process of the 2D images and estimates both posture and size of operation target in the bulk terminal based on the complemented edges. Experimental trials show that our algorithm allows us to achieve the reconstruction of hull blocks and real-time identification of operation target with high accuracy and reliability.

A novel algorithm of ship structure modeling and target identification based on point cloud for automation in bulk cargo terminals