Ellipsoid method for Simultaneous Localization and Mapping of mobile robot

Erik Zamora, Wen Yu

Resultado de la investigación: Contribución a una revistaArtículo de la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The popular extended Kalman filter SLAM (Simultaneous Localization andMapping) requires the uncertainty is Gaussian noise. This assumption is relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and on-line problems. In this paper, we use ellipsoid algorithm to SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAM in noise requirement, on-line realization, and large-scale SLAM. By bounded ellipsoid technique, we analyze the convergence and stability of the novel algorithm. Simulation and experimental results are presented that the ellipsoid SLAM is effective for on-line and large-scale problems such as Victoria Park dataset.

Idioma originalInglés
Número de artículo7040223
Páginas (desde-hasta)5334-5339
Número de páginas6
PublicaciónProceedings of the IEEE Conference on Decision and Control
Volumen2015-February
N.ºFebruary
DOI
EstadoPublicada - 2014
Evento2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, Estados Unidos
Duración: 15 dic 201417 dic 2014

Huella

Profundice en los temas de investigación de 'Ellipsoid method for Simultaneous Localization and Mapping of mobile robot'. En conjunto forman una huella única.

Citar esto