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Adaptive extended Kalman filter (AEKF)-based mobile robot localization using sonar*

机译:使用声纳*的基于自适应扩展卡尔曼滤波器(AEKF)的移动机器人定位

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摘要

In this paper, an AEKF algorithm is used to localize a mobile robot equipped with eight Polaroid sonars in an indoor structured environment. The system state equation and sonar measurement models used for locating the mobile robot are set up. The localization process based on the AEKF algorithm is given. Four criteria used to judge the validity of predictive measurements of sonars are presented, which can increase the probability of the matching between predictive measurements and actual measurements. Experi- ments show that the localization precision based on our methods is greater than that using the conventional EKF algorithm.
机译:在本文中,AEKF算法用于在室内结构化环境中定位装有八个宝丽来声纳的移动机器人。建立了用于定位移动机器人的系统状态方程和声纳测量模型。给出了基于AEKF算法的定位过程。提出了用于判断声纳预测测量结果有效性的四个标准,可以提高预测测量值与实际测量值匹配的可能性。实验表明,基于我们的方法的定位精度要高于使用传统EKF算法的定位精度。

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