基于仿鱼人工侧线的水下静态目标主动感知方法研究

Study on the Underwater Static Target Active Perception Method Based on Fish-Like Artificial Lateral Line

针对静止水域中静态目标探测问题,提出了一种基于仿鱼人工侧线的水下静态目标主动感知方法。依据流体动力学理论,分析了侧线主动感知水下静态目标的可行性。建立侧线主动感知水下静态目标的仿真模型,采集目标作用下机器鱼的体表压力数据,揭示了目标尺寸和距离对体表压强的影响关系。建立基于深度卷积神经网络的目标尺寸和距离预测回归模型,对模型结构和训练参数进行了优化。结果表明,所提出的方法可有效感知和预测水下静态目标参数。

To solve the problem of static target detection in still water,a method for underwater static target active perception is proposed based on fish-like artificial lateral line.The feasibility of lateral line actively perceiving static target is analyzed based on the theory of flu id dynamics.The simulation mode of lateral line activly perceiving static target is established and the body surface pressure data of robot fish are collected when it is affected by target.The effect of target size and distance on body surface pressure is revealed.The prediction re gression model for target size and distance based on depth convolution neural network is established,and the model structure and training parameters are optimized.The results show that the proposed method can effectively identify the underwater static target parameters.