The lateral line plays a crucial role as a sensory organ in fish for detecting and interpreting flow field environments. Taking inspiration from the lateral line of fish, this study investigates the implementation of an artificial lateral line system (ALLS) on a biomimetic fish-shaped unmanned underwater vehicle (UUV). To ensure accurate positioning of the UUV while considering physical dimensions, cost, and environmental friendliness (by avoiding the use of sonar), we propose a fusion method based on factor graph optimization that combines data from an inertial measurement unit (IMU) and the ALLS. This method integrates velocity information obtained from the artificial lateral lines with attitude information provided by the IMU, enabling the UUV to achieve precise self-positioning at a relatively low cost. Water tank experiments demonstrate the significant improvement in the UUV’s trajectory estimation ability achieved by our proposed method.

中文翻译：

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使用 IMU 和人工侧线系统的水下紧耦合状态估计方法

侧线作为鱼类的感觉器官，在检测和解释流场环境方面发挥着至关重要的作用。本研究受到鱼类侧线的启发，研究了人工侧线系统（ALLS）在仿生鱼形无人水下航行器（UUV）上的实施。为了确保 UUV 的精确定位，同时考虑物理尺寸、成本和环境友好性（通过避免使用声纳），我们提出了一种基于因子图优化的融合方法，该方法结合了来自惯性测量单元（IMU）和 ALLS 的数据。该方法将人工侧线获得的速度信息与IMU提供的姿态信息相结合，使UUV以相对较低的成本实现精确的自定位。水箱实验证明了我们提出的方法对 UUV 轨迹估计能力的显着提高。