Spatial State Analysis of Ship During Berthing and Unberthing Process Utilizing Incomplete 3D LiDAR Point Cloud Data

In smart ports, accurately perceiving the motion state of a ship during berthing and unberthing is essential for the safety and efficiency of the ship and port. However, in actual scenarios, the obtained data are not always complete, which impacts the accuracy of the ship's motion state. This paper proposes a spatial visualization method to analyze a ship's motion state in the incomplete data by introducing the GIS spatial theory. First, for the complete part under incomplete data, this method proposes a new technique named LGFCT to extract the key points of this part. Then, for the missing part under the incomplete data, this method applies the key point prediction technique based on the line features to extract the key points of this part. Note that the key points will be used to calculate the key parameters. Finally, spatial visualization and spatial-temporal tracking techniques are employed to spatially analyze the ship's motion state. In summary, the proposed method not only spatially identifies a ship's motion state for the incomplete data but also provides an intuitive visualization of a ship's spatial motion state. The accuracy and effectiveness of the proposed method are verified through experimental data collected from a ship in Dalian Port, China.