An Enhanced Particle / Kalman Filter for Robot Localization

被引：0

作者：

Mahmoud, Imbaby I. ^{[1
]}

El Tawab, Asmaa Abd ^{[1
]}

Salama, May ^{[2
]}

机构：

[1] Nucl Res Ctr, Atom Energy Author, Cairo, Egypt

[2] Benha Univ, Fac Eng, Eletron & Comm Dept, Shoubra, Banha, Egypt

来源：

2013 30TH NATIONAL RADIO SCIENCE CONFERENCE (NRSC2013) | 2013年

关键词：

Particle Filter; Kalman filter; Robot Localization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper investigates the effect of using different filters namely: Kalman filter (KF), Particle Filter (PF) and a proposed enhanced particle / Kalman (EPKF) filter based robot localizer. An algorithm is built in Matlab environment to host these filters. The performances of these filters are evaluated in terms of computational time and error from ground truth and the results are reported. The results showed that the proposed localization plan which adopts the particle filter as initialization step to Kalman filter achieves higher accuracy localization while, the computational cost is not significant.

引用

页码：338 / 346

页数：9

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