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Author Łącki, Mirosław
Affiliation Gdynia Maritime University
E-mail lacki@am.gdynia.pl
ISSN printed 1733-8670
URI https://repository.am.szczecin.pl/handle/123456789/2478
Abstract 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.
Pages 70–74
Publisher Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie
Keywords artificial intelligence
Keywords autopilot
Keywords algorithm
Keywords ship course-keeping
Keywords neuroevolution
Keywords ship maneuvering
Title Ship course-keeping with neuroevolutionary algorithms
References
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  13. Tomera, M. (2010) Nonlinear controller design of a ship autopilot. International Journal of Applied Mathematics and Computer Science 20, 2, pp. 271–280.
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ISSN on-line 2392-0378
Language English
Funding No data
Figures 6
Tables 1
DOI 10.17402/287
Published 2018-06-27
Accepted 2018-02-24
Recieved 2017-10-24


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