传感技术学报2024,Vol.37Issue(10) :1786-1794.DOI:10.3969/j.issn.1004-1699.2024.10.016

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

谢鸥 孙兆光 沈灿 陈子昂
传感技术学报2024,Vol.37Issue(10) :1786-1794.DOI:10.3969/j.issn.1004-1699.2024.10.016

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

谢鸥 1孙兆光 1沈灿 1陈子昂1
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作者信息

  • 1. 苏州科技大学机械工程学院,江苏 苏州 215009
  • 折叠

摘要

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.

Abstract

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.

关键词

人工侧线/主动感知/深度卷积神经网络/水下静态目标

Key words

artificial lateral line/active perception/depth convolution neural network/underwater static target

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基金项目

国家自然科学基金项目(51875380)

苏州市科技计划项目(SNG2017054)

出版年

2024
传感技术学报
东南大学 中国微米纳米技术学会

传感技术学报

CSTPCDCSCD北大核心
影响因子:1.276
ISSN:1004-1699
参考文献量14
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