权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Automatic Berthing System Using Artificial Neural Network

使用人工神经网络的自动靠泊系统

基本信息

批准号：
07651132
负责人：
HASEGAWA Kazuhiko
金额：
$ 1.34万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07651132/
关键词：
Ship Automatic berthing Artificial neural network Vec Twin rudder Vec Twin system Simulation 着桟操縦運動数学モデル自由航走模型船位置計測

项目摘要

Articitial neural network (ANN) is applied for automatic berthing system for ships.1) It was verified that ANN is valid for berthing control for a normal shipswith one propeller and one rudder by simulation.2) It was also applied for a ship with Vec Twin rudder system (Vec Twin ship), which has one propeller and two rudders.・Mathematical model for a Vec Twin ship was developed and verified with model experiments.・Three-Layrs ANN was configured for a Vec Twin ship.・Simulation program for manual steering of a Vec Twin ship was developed.・Simulation program was modified for easy handling and preparing the teaching data.・After learning done by ANN,three-layr ANN was found to be satisfactory in the steering of a Vec Twin ship.3) Model experiments were planned to verify the simulation.・Several methods to obtain ship position were investigated.・The accuracy of GPS was checked, using RTK-OTF (Real-Time Kinematic On the Fly) GPS system. The accuracy was found to be enough for berthing manoeuvres. However, it is still very expensive to use it now.・Investigation and research on image processing position measuring system should be done further.・Ultra-sonic position measuring system is hard for the purpose of automatic berthing.・In the future, the model experiments using ANN are planned based on these investigations.

本文将人工神经网络应用于船舶自动靠泊系统。1）通过仿真验证了人工神经网络对单桨单舵船舶的靠泊控制是有效的。2）将人工神经网络应用于一艘单桨双舵船舶（Vec Twin ship）的靠泊控制。建立了Vec Twin船的数学模型，并通过模型试验进行了验证。三层人工神经网络被配置用于Vec Twin飞船。·开发了Vec Twin船手动操纵仿真程序。·修改了模拟程序，以便于操作和准备教学数据。·通过神经网络的学习，发现三层神经网络在Vec Twin船的操纵中是令人满意的。3）计划进行模型实验以验证仿真。研究了获取船舶位置的几种方法。·利用RTK-OTF（Real-Time Kinematic On the Fly）GPS系统对GPS的精度进行了检验。准确性被认为是足够的停泊机动。但是，现在使用它仍然非常昂贵。·对图像处理位置测量系统的研究有待进一步深入。超声波船位测量系统是船舶自动靠泊的重要手段。在未来，使用人工神经网络的模型实验计划在这些调查的基础上。