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

Zunif Ermayanti, E. Apriliani, H. Nurhadi, T. Herlambang
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引用次数: 39

Abstract

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%.
基于确定轨迹的自主水下机器人位置估计与控制采用模糊卡尔曼滤波方法
无人水下航行器(UUV),也被称为水下无人驾驶飞机,是任何能够在水下无人操作的交通工具。AUV (Autonomous Underwater Vehicle,自主水下航行器)是一种不依赖人类直接输入而独立运行的航行器。这种AUV需要有一个导航系统,可以操纵6个自由度(DOF),并能够根据确定的轨迹估计准确的位置。采用模糊卡尔曼滤波(FKF)方法估计水下机器人的位置。这个过程是用来保持轨迹的准确性。FKF算法在几种弹道情况下的性能表明,该方法具有较小的均方根误差(RSME),小于10%。
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