Estimation of berthing state of maritime autonomous surface ships based on 3D LiDAR

During the process of automatic berthing, the maritime autonomous surface ship (MASS) needs to sense its own status relative to the berth in real-time and accurately to avoid collisions. This study proposes a berthing state perception method based on 3D LiDAR for MASS. First, a method for estimating the ship state based on point cloud registration is established. The accuracy of this method is verified through a comparison with GPS/IMU integrated navigation. Then, the detailed calculation methods for five types of berthing status are proposed, which including the distance, transversal velocity, longitudinal velocity, vessel-approaching angle and yaw rate. Besides, a berthing perception framework based on the robot operation system (ROS) is constructed. Finally, a test platform was established, and berthing experiments were conducted. The experimental results indicated that the average relative error between the calculated results of the berthing state perception method and actual measured value is 2.85%, with a calculation frequency of 10 Hz, which meets the accuracy and real-time requirements of the ship berthing sensing. The method proposed in this paper can not only assist other perception units, such as GPS/IMU, to form a redundant sensing system, but also provide accurate and real-time berthing status information for the control unit.