Summary
International Symposium on Nonlinear Theory and its Applications
2005
Session Number:3-1-5
Session:
Number:3-1-5-5
Localization of Cyber Rodent Based on Mixture Kalman Filters
Michiyuki Magono, Junichiro Yoshimoto, Shin Ishii, Kenji Doya,
pp.401-404
Publication Date:2005/10/18
Online ISSN:2188-5079
Summary:
Self-localization is one of important topics in the field of mobile robotics. This article presents a localization method based on a Bayesian approach for Cyber Rodent, which is a rodent-like mobile robot. In our method, the state transition and the sensory characteristics are formulated as a linear-Gaussian model with a redundant dimension and a probabilistic RBF network, respectively. By applying a recursive Bayesian inference, the localization algorithm is derived as a variant of mixture Kalman filters. Computer simulation results demonstrate the accuracy and the effectiveness of our method, as compared with a Monte Carlo localization based on a particle filter technique.