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Dr. May ahmed salama mohamed :: Publications:

Title:
Appraisal of Different Particle Filter Resampling Schemes Effect in Robot Localization
Authors: Imbaby I. Mahmoud, Asmaa Abd El Tawab, May Salama and Howida A. Abd El-Halym
Year: 2012
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: Local
Paper Link:
Full paper May ahmed salama mohamed_Appraisal.pdf
Supplementary materials Not Available
Abstract:

This paper considers the effect of the Resampling schemes in the behavior of Particle Filter (PF) based robot localizer. The investigated schemes are Multinomial Resampling, Residual Resampling, Residual Systematic Resampling, Stratified Resampling and Systematic Resampling. An algorithm is built in Matlab environment to host these schemes. The performances are evaluated in terms of computational complexity and error from ground truth and the results are reported. The results showed that the localization plan which adopts the Systematic or Stratified Resampling scheme achieves higher accuracy localization while decreasing consumed computational time. However, the difference is not significant. Moreover, a particle excitation strategy is proposed. This strategy achieved significant improvement in the behavior of PF based robot localization.

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