中文摘要：

无人水下航行器（Unmanned undersea vehicle,UUV）是水下作业探测中一种应用广泛的工具,它能否很好地适应水下环境对其远距离正常工作有着重要影响。与水下鱼类对比,机器人与水下环境间的交互能力相去较远,其中尤以水下机器人对海洋环境的水流特征识别最为重要。传统UUV在水下的控制运行必须消耗大量能量维持状态与运行,这种被动应对环境的方式具有很大的不足,也对无线遥控水下机器人的生存造成障碍。因此,水下机器人能否正确感知水流是其能否进一步探索利用海洋的重要因素。研究发现,鱼类的侧线系统可感知水流,并辅助运动规划。研究鱼类侧线感知水流的机理,针对鱼雷型UUV的不同水流环境,使用计算流体动力学方法提取本体压力数据,选择线性判别分析与支持向量机技术训练并建立水流感知分类模型,从功能角度仿生侧线感应水流能力。模型测试表明,不同的水流工况下UUV识别到不同模式,可进行本体周围水况区分度辨识,为水下机器人识别水流环境与利用海洋提供一种新的视度。

英文摘要：

Unmanned undersea vehicle（UUV） is a tool widely used in underwater detection. It is the crucial factor for UUV to work well in deep underwater environment. With a view to the problems of the capability of robot to percept the underwater situation compared with fish, an model that can identify the flow characteristic of the water is presented. The control of robot must consume large amounts of energy to maintain the position and status traditionally, which is passive and dangerous for UUV to cope with the challenge in the water. Therefore, it is very important for underwater vehicles to recognize current and explore ocean further. Studies on the lateral line system show that it can distinguish the flow of water and improve the motion of the fish. Aimed at a torpedo UUV, the mechanism and capability of lateral line system is studied and realized using the pressure data of vehicle calculated by CFD software. The linear discriminant analysis and support vector machine methods are selected to establish the flow sensing classification model. The tests demonstrate that the method can identify different flows around the vehicle effectively and can provide a new view for the study of underwater vehicle during the development and use of ocean.