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Estimate and control position autonomous Underwater Vehicle based on determined trajectory using Fuzzy Kalman Filter method

机译:基于模糊卡尔曼滤波法的基于确定轨迹的估计和控制位置自主水下车辆

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Unmanned Underwater Vehicle (UUV), known as underwater drones, are any vehicle that are able to operate underwater without human occupant. AUV (Autonomous Underwater Vehicle) are one of categories of these vehicles which operate independently of direct human input. This AUV is required to have a navigation system that can manoeuvred 6 Degree of Freedom (DOF) and able to estimate the exact position based on the determined trajectory. Fuzzy Kalman Filter (FKF) method is used to estimate the position of the AUV. This process is used to maintain the accuracy of the trajectory. The performance of FKF algorithm on some several trajectory cases show that this method has relatively small Root Means Square Error (RSME), which is less than 10%.
机译:无人驾驶的水下车辆(UUV)被称为水下无人机,是任何能够在没有人类占用者的水下操作的车辆。 AUV(自主水下车辆)是这些车辆的类别之一,其独立于直接人类投入运营。该AUV需要具有可以操纵6自由度(DOF)的导航系统,并且能够基于所确定的轨迹估计精确位置。模糊卡尔曼滤波器(FKF)方法用于估计AUV的位置。该过程用于保持轨迹的准确性。 FKF算法在一些轨迹案例上的性能表明,该方法具有相对较小的根部误差(RSME),其小于10%。

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