| publication name | An Enhanced Particle / Kalman Filter for Robot Localization |
|---|---|
| Authors | Imbaby I. Mahmoud, Asmaa Abd El Tawab , May Salama |
| year | 2013 |
| keywords | |
| journal | |
| volume | Not Available |
| issue | Not Available |
| pages | Not Available |
| publisher | Not Available |
| Local/International | Local |
| Paper Link | Not Available |
| Full paper | download |
| 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.