Development of Automatic Ship Berthing System Using Artificial Neural Network and Distance Measurement System

Abstract

In the studies on an berthing control of ship, an artificial neural network (ANN) model is commonly employed as the main controller to control the rudder and the propeller. The existing ANN controllers that use the parameters consisting of the ship position and the ship heading as inputs cannot be applied to control automatically the ship into berth in different ports. To deal with this problem, the parameters, such as relative bearing and distance from ship to berth calculated by radar can be used as inputs for the controller. However, the calculation of these factors is not accurate because some errors arise on using radar for berthing process. This leads to the lack of confidence in ship berthing system using the parameters determined by radar. In this research, the neural network based-automatic berthing system is developed for ship by using the parameters which are measured by distance measurement system. By this proposed system, the ship is brought automatically into berth in different ports without retraining the neural network. In addition, this system guarantees that the parameters used for inputs of the neural network is measured exactly and continually. To validate the proposed algorithm, numerical simulations are carried out to two imaginary ports and a real port, and result showed the good performance of the proposed system for automatic ship berthing.

Automatic Ship Berthing Based on Fuzzy Logic

“…To automatize the ship berthing process in future, many studies have been performed to develop this system. In researches of [1,3,[5][6][7]9], neural network controllers were proposed to automatically maneuver the ship by changing the ship's rudder and propeller. The principle of those controllers is to mimic actions which are trained by teaching data in advance.…”

“…However, the use of inputs in head-up coordinate system commonly contains the errors by radar onboard the ship. To overcome the limitations of head-up coordinate system, Nguyen et al [6] suggested a neural controller with new inputs which are determined by distance measurement system. In comparison with the head-up coordinate system based controller, the proposed controller in this research is more confident and it can be applied for unmanned ship in future.…”

“…In comparison with the head-up coordinate system based controller, the proposed controller in this research is more confident and it can be applied for unmanned ship in future. Although, the above mentioned researches [1][2][3][4][5][6] contributed the significant results to ship berthing, they only focused on how to maneuver automatically the ship from fair-way area to wharf area but not wharf position.…”

Research on a Support System for Automatic Ship Navigation in Fairway

“…As developed by the authors in Reference [29], a virtual window was used to create instructive data for the controller. Berthing at different ports is recorded in References [30,31]. Another approach, which examined via the research in Reference [32], used an adaptive back-stepping control for a cruise ship under wind power.…”

“…At this point, the ship control process is changed into automatic berthing mode with low speed ship motion. The berthing problem noted in researches [27][28][29][30][31] can adapt to the proposed navigation system. In Figure 12, the automatic berthing process described in References [27][28][29][30][31] uses a neural network controller to regulate the rudder angle and the propeller revolution simultaneously.…”