A fast recognition algorithm of ship hatch in bulk cargo terminal based on point cloud contour extraction

Abstract

Port loading automation systems can improve the efficiency of cargo transfer, save port operation time and create greater economic benefits. The recognition of ship hatch is the basis and premise of building an automatic loading system, it is a major time cost in the loading system meanwhile. How to identify the hatch quickly and accurately is an important problem that needs to be solved urgently under the actual production needs of ports. In order to save the time of ship hatch recognition, this paper proposes a fast hatch recognition algorithm based on point cloud contour extraction. The ship point cloud model generated by lidar scanning is preprocessed to remove the noise and isolated points in the model. Projecting the preprocessed point cloud on the XOY plane, converting the three-dimensional point cloud into a two-dimensional image, extracting the outline further getting the point cloud pixels with linear features of the two-dimensional image by α − shape algorithm. Projecting the feature point cloud to the X-axis to classify the hatches. According to the center point of each class of point cloud, searching for the nearest neighbor hatch edge feature points to calculate hatch coordinates in the world frame. An experimental study was carried out on the scan data of actual docked ships at Guoneng Tianjin Port. The results show that the algorithm can realize the hatch recognition quickly which the speed is increased by 424% compared with the previous algorithm and the identification accuracy meets the actual production needs of the port.