Staff Members - Benha University
An Enhanced Particle / Kalman Filter for Robot Localization
• 2013
Publication Information
Authors
Imbaby I. Mahmoud, Asmaa Abd El Tawab , May Salama
Keywords
Not Available
Journal
Not Available
Publisher
Not Available
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
Local
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
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.
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.