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Wyszukujesz frazę "navigation and control (GNC)" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Is full-autonomy the way to go towards maximizing the ocean potentials?
Autorzy:
Zghyer, R.
Ostnes, R.
Halse, K. H.
Powiązania:
https://bibliotekanauki.pl/articles/116079.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
autonomous vessel
hydrodynamics
guidance
navigation and control (GNC)
human factor
remote control
full-authonomy
levels of automation (LOA)
automation
Opis:
Growth prospects for ocean economy are promising because ocean industries are addressing challenges such as food security, energy security and climate change. However, safety and efficiency are the general challenges of ocean operations. Increased automation is believed to solve these problems. This paper discusses the impact of automation on safety and efficiency. A literature review of ‘Human factors’ mainly from the aviation and maritime industries is presented to untangle the human-machine relationship characteristics when increased automation is introduced to operators. A literature review of Hydrodynamics, Guidance, Navigation and Control (GNC) technologies is presented to introduce the state-of-art and associated limitations. It is concluded that, if the industry’s drive is safety and efficiency, then full-autonomy is, at present, not the way to go. Remote control, instead, could facilitate a feasible future, while focused research and development are in need.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2019, 13, 1; 33-42
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-criteria ACO-based algorithm for ship’s trajectory planning
Autorzy:
Lazarowska, A.
Powiązania:
https://bibliotekanauki.pl/articles/116548.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
colregs
ships manoeuvering
Ant Colony Optimization (ACO)
ship’s trajectory planning
route planning
multi-criteria ACO-based algorithm
guidance
navigation and control (GNC)
ARPA
Opis:
The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a multi-criteria optimization task. The criteria taken into account during problem solving are: path safety, path length, the International Regulations for Preventing Collisions at Sea (COLREGs) compliance and path smoothness. The paper includes the description of the new multi-criteria ACO-based algorithm along with the presentation and discussion of simulation tests results.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 1; 31-36
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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