The navy and other Department of Defense organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. The term USV refers to any vehicle that operates on the surface of the water without a crew. USVs have the potential, and in some cases the demonstrated ability, to reduce risk to manned forces, provide the necessary force multiplication to accomplish military missions, perform tasks which manned vehicles cannot, and do so in a way that is affordable for the navy. A survey of USV activities worldwide as well as the general technical challenges of USVs was presented below. A general description of USVs was provided along with their typical applications. The technical challenges of developing a USV include its intelligence level, control, high stability, and developmental cost reduction. Through the joint efforts of researchers around the world, it is believed that the development of USVs will enter a new phase in the near future, as USVs could soon be applied widely both in military and civilian service.

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Drag estimation and shape optimization of autonomous underwater vehicle (AUV) hulls are critical to energy utilization and endurance improvement. In the present work, a shape optimization platform composed of several commercial software packages is presented. Computational accuracy, efficiency and robustness were carefully considered and balanced. Comparisons between experiments and computational fluid dynamics (CFD) were conducted to prove that a two-dimensional (2D) unstructured mesh, a standard wall function and adaptive mesh refinement could greatly improve efficiency as well as guarantee accuracy. Details of the optimization platform were then introduced. A comparison of optimizers indicates that the multi-island genetic algorithm (MIGA) obtains a better hull shape than particle swarm optimization (PSO), despite being a little more time consuming. The optimized hull shape under general volume requirement could provide reference for AUV hull design. Specific requirements based on optimization testify of the platform's robustness.

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