计算机应用研究2009，Vol.26Issue(8)：2974-2976,3.DOI:10.3969/j.issn.1001-3695.2009.08.051
基于模糊自适应卡尔曼滤波的移动机器人定位方法
Localization of mobile robot based on fuzzy-adapted Kalman filtering
摘要
Abstract
In order to resolve the problem of mobile robot localization with unknown noise characteristics, this paper proposed a mobile robot localization method based on fuzzy-adapted extended Kalman filtering. Combined fuzzy logic and covariance-matching technique together to adjust the measurement noise covariance R and on-line improve the performance of the localization algorithm. Moreover, it used a sensor fault diagnostic and recovery algorithm to monitor the sensors' states and improved the algorithm's robustness. Then applied the algorithm to mobile robot localization with unknown measurement noise characteristics. Experimental results show that this method can effectively reduce the effect of incomplete a prior knowledge of R, and improve the localization accuracy.关键词
移动机器人定位/扩展卡尔曼滤波/模糊理论/协方差匹配Key words
mobile robot localization/extended Kalman filtering/fuzzy logic/covariance-matching分类
信息技术与安全科学引用本文复制引用
徐海伟,殷波,徐涛..基于模糊自适应卡尔曼滤波的移动机器人定位方法[J].计算机应用研究,2009,26(8):2974-2976,3.基金项目
青岛市科技攻关资助项目(06-2-2-10-jch) （06-2-2-10-jch）
