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Technical Program

Paper Detail

Paper:	SPTM-L1.5
Session:	Bayesian Approaches and Particle Filters
Time:	Tuesday, May 16, 11:50 - 12:10
Presentation:	Lecture
Topic:	Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications
Title:	MOBILE ROBOT LOCALIZATION USING IMPROVED SIR FILTERS AND PARAMETRIC MODELS OF THE ENVIRONMENT
Authors:	Paulo Roberto Silva, Marcelo Bruno, Instituto Tecnologico de Aeronautica, Brazil
Abstract:	We introduce in this paper an improved particle filter for mobile robot localization using a parametric model of the environment. The proposed filter combines a clutter suppression routine for feature extraction with an optimized importance function and measurement-driven MCMC move steps. The filter is tested with both real and synthetic data and its performance is compared to competing algorithms found in the literature.