Mobile robot localization based on Extended Kalman Filter

被引：0
|
作者：
Kong, Fantian [1 ]
Chen, Youping [1 ]
Xie, Jingming [1 ]
Zhang, Gang [1 ]
Zhou, Zude [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan, Hubei Prov, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
基金：
中国国家自然科学基金;
关键词：
mobile robot; localization; extended kalman filter;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The mobile robot localization methodologies in common use at present have been introduced. A localization algorithm based on Extended Kalman Filter (EKF) has been proposed on the basis of environment feature extraction and map building, which can reduce the error in the calculation of the robot's position and orientation. The method is that the mobile robot analyses and fuses the messages in surroundings from multiple sensors by EKF theory, which enables the robot to identify the surrounding objects clearly and guide itself successfully. The simulation and experimental results show that the proposed localization method is effective.
引用
收藏
页码：220 / 220
页数：1
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