Title :
Practical application of an evolutionary algorithm for the design and construction of a six-inch submarine
Author :
Alam, Khairul ; Ray, Tapabrata ; Anavatti, Sreenatha G.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Abstract :
Unmanned underwater vehicles (UUVs) are becoming an attractive option for maritime search and survey operations as they are cheap and efficient compared to conventional use of divers or manned submersibles. Consequently, there has been a growing interest in UUV research among scientific and engineering communities. Although UUVs have received significant research interest in recent years, limited attention has been paid towards design and development of mini/micro UUVs (usually less than 1 foot in length). Micro unmanned underwater vehicles (μUUVs) are particularly attractive for deployment in extraordinarily confined spaces such as inspection of intricate underwater structures, ship wrecks, oil pipe lines or extreme hazardous areas. This paper considers previous work done in the field of miniature UUVs and presents an optimization framework for preliminary design of that class of UUVs. A state-of-the-art optimization algorithm namely infeasibility driven evolutionary algorithm (IDEA) is used to carry out optimization of the μUUV designs. The framework is subsequently used to identify optimal design of a torpedo-shaped μUUV with an overall length of six inches (152.4 mm). The preliminary design identified through the process of optimization is further analyzed with the help of a computer-aided design tool to come up with a detailed design. The final design has since then been built and is currently undergoing trials.
Keywords :
autonomous underwater vehicles; evolutionary computation; underwater vehicles; IDEA; UUV design; infeasibility driven evolutionary algorithm; microunmanned underwater vehicles; miniature UUV; optimization algorithm; six-inch submarine; torpedo-shaped μUUV; Cameras; Drag; Geometry; Optimization; Shape; Underwater vehicles; Vehicles;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900264