A Comparative Analysis of Particle Filter Based Localization Methods

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Luca Marchetti, Giorgio Grisetti, Luca Iocchi

Published: 01 Jan 2006, Last Modified: 18 Jun 2024RoboCup 2006EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Self-localization is a deeply investigated field in mobile robotics, and many effective solutions have been proposed. In this context, Monte Carlo Localization (MCL) is one of the most popular approaches, and represents a good tradeoff between robustness and accuracy. The basic underlying principle of this family of approaches is using a Particle Filter for tracking a probability distribution of the possible robot poses.