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Title
Ship course-keeping with neuroevolutionary algorithms

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Łącki, Mirosław1
URI: https://repository.am.szczecin.pl/handle/123456789/2478
2018-06-27
The goal of research presented in this article is to check if a neuroevolutionary method with direct encoding is able to be a part of autopilot of the vessel. One of the important tasks of vessel autopilots is to keep a course as straight as possible or to bring the ship back on the route as efficiently as possible. In this paper, the adaptive neuroevolutionary autopilot is described and tested on a simulation model of a ferry. Neuroevolution is a combination of two different but related fields of artificial machine learning: evolution and neural networks. The combined method is very flexible and can be applied to other ship control tasks. The results of computer simulation of the neuroevolutionary course-keeping system have been included.
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Title

Ship course-keeping with neuroevolutionary algorithms

Pages

70–74

Figures

6

Tables

1

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

10.17402/287

Type

Journal

54 Scientific Journals of the Maritime University of Szczecin, no. 54 / 2018

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Published

2018-06-27

Recieved

2017-10-24

Accepted

2018-02-24

Funding

No data

Keywords

artificial intelligence, autopilot, algorithm, ship course-keeping, neuroevolution, ship maneuvering

URI:

https://repository.am.szczecin.pl/handle/123456789/2478

Language

English

Authors

Łącki, Mirosław1

Affiliation

1 Gdynia Maritime University, lacki@am.gdynia.pl

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