个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:Vice Dean of School of Control Science and Engineering
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:控制科学与工程学院
学科:模式识别与智能系统. 控制理论与控制工程. 导航、制导与控制. 人工智能
办公地点:大连理工大学 创新园大厦 A611室
联系方式:办公电话:0411-84707581
电子邮箱:zhuang@dlut.edu.cn
A robust extended H-infinity filtering approach to multi-robot cooperative localization in dynamic indoor environments
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论文类型:期刊论文
发表时间:2013-07-01
发表刊物:CONTROL ENGINEERING PRACTICE
收录刊物:SCIE、EI、Scopus
卷号:21
期号:7
页面范围:953-961
ISSN号:0967-0661
关键字:Multi-robot cooperative localization; Robust extended H-infinity filtering (REHF); Metric-based Iterative Closest Point (MbICP); Laser data interaction
摘要:Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H-infinity filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment. (C) 2013 Elsevier Ltd. All rights reserved.