Development of Modular Bio-Inspired Autonomous Underwater Vehicle for Close Subsea Asset Inspection

Клики: 205
ID: 269922
2021
Метрики качества и эффективности статьи
Общее качество Improving Quality
0.0 /100
Объединяет данные вовлечённости с оценкой академического качества ИИ
Оценка качества ИИ
Не проанализировано
Аннотация
To reduce human risk and maintenance costs, Autonomous Underwater Vehicles (AUVs) are involved in subsea inspections and measurements for a wide range of marine industries such as offshore wind farms and other underwater infrastructure. Most of these inspections may require levels of manoeuvrability similar to what can be achieved by tethered vehicles, called Remotely Operated Vehicles (ROVs). To extend AUV intervention time and perform closer inspection in constrained spaces, AUVs need to be more efficient and flexible by being able to undulate around physical constraints. A biomimetic fish-like AUV known as RoboFish has been designed to mimic propulsion techniques observed in nature to provide high thrust efficiency and agility to navigate its way autonomously around complex underwater structures. Building upon advances in acoustic communications, computer vision, electronics and autonomy technologies, RoboFish aims to provide a solution to such critical inspections. This paper introduces the first RoboFish prototype that comprises cost-effective 3D printed modules joined together with innovative magnetic coupling joints and a modular software framework. Initial testing shows that the preliminary working prototype is functional in terms of water-tightness, propulsion, body control and communication using acoustics, with visual localisation and mapping capability.
Ссылочный ключ
gorma2021applieddevelopment Используйте этот ключ для автоцитирования в рукописи при использовании SciMatic Manuscript Manager или Thesis Manager
Авторы Wael Gorma;Mark A. Post;James White;James Gardner;Yang Luo;Jongrae Kim;Paul D. Mitchell;Nils Morozs;Marvin Wright;Qing Xiao;Gorma, Wael;Post, Mark A.;White, James;Gardner, James;Luo, Yang;Kim, Jongrae;Mitchell, Paul D.;Morozs, Nils;Wright, Marvin;Xiao, Qing;
Журнал applied sciences
Год 2021
DOI
10.3390/app11125401
URL
Ключевые слова

Цитирования

Цитирования не найдены. Чтобы добавить цитирование, свяжитесь с администратором по адресу info@scimatic.org

Комментариев пока нет. Будьте первым, кто прокомментирует эту статью.