A MPF Based Distributed Method for Mobile Robot and Wireless Sensor Nodes Simultaneous Localization

被引：0
作者：
Kong Liang [1 ,2 ,3 ]
Kong Lingfu [2 ]
Wu Peiliang [2 ]
Li Yuerong [1 ]
机构：
[1] Hebei Normal Univ Sci & Technol, Coll Math & Informat Technol, Qinhuangdao 066004, Peoples R China
[2] Yanshan Univ, Coll Informat Sci & Engn, Qinhuangdao 066004, Peoples R China
[3] Hebei Normal Univ Sci & Technol, Inst Math & Syst Sci, Qinhuangdao, Peoples R China
来源：
PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE | 2012年
关键词：
Simultaneous Localization; Marginal Particle Filter; Unscented Kalman Filter; Mobile Robot; Wireless Sensor Node;
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：
A MPF based distributed method for mobile robot and wireless sensor nodes simultaneous localization is proposed to solve the problem that localization based on the simple particle filter suffers from severe sample degeneracy . In the proposed method, the proposal distribution of each particle is estimated by UKF, and the observations between wireless sensor nodes are used to estimate a sensor node's location. Simulation results show that the proposed method can increase the sample variety and reduce sample degeneracy, and is much more accurate, compared with distributed localization based on the simple particle filter. Moreover, the estimation accuracy of the proposed method is still good with few sample. Therefore, it is feasible to improve the computational efficiency by reducing the number of particles.
引用
收藏
页码：4895 / 4899
页数：5
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