Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
This paper is dedicated to an overview of components of an onboard control system of an autonomous ship. This system controls and operates the ship. Therefore, this system needs to be able to analyze the ship’s state, predict its future development and analyze the consequences of its own decisions. The paper focuses on software aspects of the onboard control system, not the hardware. The paper provides an overview of technologies that can be used to implement the components of such a system responsible for planning new routes, handling the ship during the voyage, ensuring its seaworthiness and safety during the voyage, monitoring an autonomous ship from an onshore control centre, ensuring the robustness of the onboard control system, and collective operations of multiple autonomous ships. The paper describes benefits the maritime industry would gain from deploying some of the technologies developed for autonomous ships on ordinary, human-controlled ships. The paper also describes some challenges, especially in the field of automatic decision and reasoning, arising from the emergence of autonomous and smart ships. The main contribution of the paper is that it summarizes existing research in different areas of autonomous ship technology.
Rocznik
Tom
Strony
611--619
Opis fizyczny
Bibliogr. 48 poz., rys.
Twórcy
autor
- State Marine Technical University, Saint-Petersburg, Russia
autor
- State Marine Technical University, Saint-Petersburg, Russia
Bibliografia
- [1] Osman Balci. Validation, verification, and testing techniques throughout the life cycle of a simulation study. Annals of Operations Research, 53(1):121– 173, Dec 1994.
- [2] Osman Balci. Verification, validation, and accreditation. In Proceedings of the 30th Conference on Winter Simulation, WSC ’98, pages 41–4, Los Alamitos, CA, USA, 1998. IEEE Computer Society Press.
- [3] C.L. Benson, P.D. Sumanth, and A. P. Colling. A quantitative analysis of possible futures of autonomous transport. In INEC 2018 Conference, 2018.
- [4] Lars Bergdahl. Comparison of measured shallowwater wave spectra with theoretical spectra. Proceedings of the 8th European Wave and Tidal Energy Conference, Uppsala, Sweden, 2009, 2009.
- [5] Phil Bernstein, Sergey Bykov, Alan Geller, Gabriel Kliot, and Jorgen Thelin. Orleans: Distributed Virtual Actors for Programmability and Scalability. March 2014.
- [6] Mogens Blanke, Michael Henriques, and Jakob Bang. A pre-analysis on autonomous ships. Technical University of Denmark, 2016.
- [7] E. Cantu´-Paz. A survey of parallel genetic algorithms. CALCULATEURS PARALLELES, RESEAUX ET SYSTEMS REPARTIS, (10), 1998.
- [8] A. Castro, R. Carballo, G. Iglesias, and J.R. Rabun˜al. Performance of artificial neural networks in nearshore wave power prediction. Applied Soft Computing, 23:194 – 201, 2014.
- [9] Dominik Charousset, Thomas C. Schmidt, Raphael Hiesgen, and Matthias Wa¨hlisch. Native Actors– A Scalable Software Platform for Distributed, Heterogeneous Environments. In Proc. of the 4rd ACM SIGPLAN Conference on Systems, Programming, and Applications (SPLASH ’13), Workshop AGERE!, pages 87–96, New York, NY, USA, Oct. 2013. ACM.
- [10] Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, and Yan Liu. Recurrent neural networks for multivariate time series with missing values. Scientific Reports, 8(1):6085, 2018
- [11] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms. MIT Press and McGraw-Hill, 2009.
- [12] John F. Cross and Gordon Meadow. Autonomous ships 101. Journal of Ocean Technology, Vol 12:23– 27, 09 2017.
- [13] V. I. Dmitriev and V. V. Karetnikov. Methods of ensuring the safety of navigation when implement unmanned technology (in russian). Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova 9.6 (2017), 2017.
- [14] Global Maritime Engineering. Hull Stress Monitoring System Electric Sensors’ Solution. Measure stresses, torsions, caused by Waves, Cargo Operations and Motions.
- [15] Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT Press, 2016. http://www.deeplearningbook.org.
- [16] M. Grifoll, F. X. Mart´ınez de Ose´s, and M. Castells. Potential economic benefits of using a weather shiprouting system at short sea shipping. WMU Journal of Maritime Affairs, 17(2):195–211, Jun 2018.
- [17] Manel Grifoll, Llu´ıs Martorell, Marcel·la Castells, and Francesc Xavier Mart´ınez de Ose´s. Ship weather routing using pathfinding algorithms: the case of Barcelona – Palma de Mallorca. In XIII Congreso de Ingenieria del Transporte, pages 1–11. Universidad de Oviedo, 2018.
- [18] A. Hassani and J. Treijs. An overview of standard and parallel genetic algorithms. IDT workshop on interesting results in computer science and engineering, 2009.
- [19] Klaus Hasselmann, T. Barnett, E. Bouws,H. Carlson, D. Cartwright, K Enke, J Ewing, H Gienapp, D. Hasselmann, P. Kruseman, A Meerburg, Peter Muller, Dirk Olbers, K Richter, W. Sell, and H. Walden. Measurements of wind-wave growth and swell decay during the joint north sea wave project (jonswap). Deut. Hydrogr. Z., 8:1–95, 01 1973.
- [20] John H. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI, 1975. second edition, 1992.
- [21] Rolls-Royce Ship Intelligence. Autonomous ships. the next step. Rolls-Royce Marine, 2016.
- [22] Alex Irpan. Deep reinforcement learning doesn’t work yet. https://www.alexirpan.com/2018/02/14/ rlhard.html, 2018.
- [23] Hinnenthal Jo¨rn and Harries Stefan. A systematic study on posing and solving the problem of pareto optimal ship routing. In 3rd International Conference on Computer and IT Applications in the Maritime Industries, COMPIT’04, pages 27–36, 2004.
- [24] V. V. Karetnikov, I. V. Pashchenko, and A. I. Sokolov. Prospects of introducing unmanned navigation on inland waterways of the Russian Federation (in russian). Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova 9.3 (2017), 2017.
- [25] Abdullah Konak, David W. Coit, and Alice E. Smith. Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91(9):992 – 1007, 2006. Special Issue Genetic Algorithms and Reliability.
- [26] Leslie Lamport. Time, clocks, and the ordering of events in a distributed system. Commun. ACM, 21(7):558–565, jul 1978.
- [27] Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature, 521:436 EP, May 2015.
- [28] R. Leigh, S. J. Louis, and C. Miles. Using a genetic algorithm to explore a*-like pathfinding algorithms. In 2007 IEEE Symposium on Computational Intelligence and Games, pages 72–79, April 2007.
- [29] Hugh McKee and Oliver White. Akka A to Z. An Architect’s Guide To Designing, Building, And Running Reactive Systems. Lightbend, Inc., 2018.
- [30] Yu. I. Nechaev. Catastrophe theory: the modern approach to decision-making (in Russian). ArtExpress, Saint-Petersburg, 2011.
- [31] Yuri I. Nechaev and Oleg N. Petrov. Intellectual technology for control of dynamic unsinkability on the unmanned vessels (in Russian). Marine intellectual technologies, 3(1), 2020.
- [32] Nikitas Nikitakos. Fourth industrial revolution in maritime sector. University of the Aegean, 2019.
- [33] Masoud Nosrati, Ronak Karimi, and Hojat Allah Hasanvand. Investigation of the * (star) search algorithms: Characteristics, methods and approaches. World Applied Programming, 2(4):251–256, April 2012.
- [34] Diego Ongaro and John Ousterhout. In search of an understandable consensus algorithm. In 2014 USENIX Annual Technical Conference (USENIX ATC 14), pages 305–319, Philadelphia, PA, jun 2014. USENIX Association.
- [35] Lokukaluge Perera. Deep learning towards autonomous ship navigation and possible colregs failures. Journal of Offshore Mechanics and Arctic Engineering, 05 2019.
- [36] Alexandr Pinskiy. E-navigation and autonomous ship handling (in russian). Transport of the Russia Federation. A journal about science, practice, economics, 2016.
- [37] MUNIN Project. Research in maritime autonomous systems project results and technology potentials, 02 2016.
- [38] Wei Shao, Peilin Zhou, and Sew Kait Thong. Development of a novel forward dynamic programming method for weather routing. Journal of Marine Science and Technology, 17(2):239–251, Jun 2012.
- [39] David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis. Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587):484–489, Jan 2016.
- [40] David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, and Demis Hassabis. Mastering chess and shogi by self-play with a general reinforcement learning algorithm. CoRR, abs/1712.01815, 2017.
- [41] Martin Hjorth Simonsen, Erik Larsson, Wengang Mao, and Jonas W. Ringsberg. State-of-the-art within ship weather routing. In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering, page 11, 2015.
- [42] Alexander N. Suslov, Olga V. Odegova, and Sun Tanshi. Approaches for the stability automation monitoring creation (in Russian). Marine intellectual technologies, 3(1), 2020.
- [43] K. Takashima, B. Mezaoui, and R. Shoji. On the Fuel Saving Operation for Coastal Merchant Ships using Weather Routing. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 3:401–406, 2009.
- [44] Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michae¨l Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander S. Vezhnevets, Re´mi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom L. Paine, Caglar Gulcehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wu¨nsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, and David Silver. Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature, 575(7782):350–354, Nov 2019
- [45] Anna Ja. Voitkunskaia and Petr N. Zvyagin. A routing of a vessel in drifting ice (in russian). In Marine Intellectual Technologies. Proceedings of the SaintPetersburg State Marine Technical University., volume 2 (40), 1, pages 166–172, 2018.
- [46] Liwei Wang, Yin Li, and Svetlana Lazebnik. Learning two-branch neural networks for image-text matching tasks. CoRR, abs/1704.03470, 2017.
- [47] Wa¨rtsila¨. Stress monitoring system, hull stress surveillance system. In Wa¨rtsila¨ Encyclopedia of Marine Technology, 2020.
- [48] Haimin Yang, Zhisong Pan, and Qing Tao. Robust and adaptive online time series prediction with long shortterm memory. Computational Intelligence and Neuroscience, 2017:1–9, 12 2017.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d6df5759-62b8-4aa9-b883-3e113fbfbf9e