Ellipsoid method for Simultaneous Localization and Mapping of mobile robot

Erik Zamora; Wen Yu

doi:10.1109/CDC.2014.7040223

Ellipsoid method for Simultaneous Localization and Mapping of mobile robot

Unidad Profesional Interdisciplinaria de Ingeniería y Tecnologías Avanzadas (UPIITA)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión 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 original	Inglés
Título de la publicación alojada	53rd IEEE Conference on Decision and Control,CDC 2014
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	5334-5339
Número de páginas	6
Edición	February
ISBN (versión digital)	9781479977468
DOI	https://doi.org/10.1109/CDC.2014.7040223
Estado	Publicada - 2014
Evento	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, Estados Unidos Duración: 15 dic. 2014 → 17 dic. 2014

Serie de la publicación

Nombre	Proceedings of the IEEE Conference on Decision and Control
Número	February
Volumen	2015-February
ISSN (versión impresa)	0743-1546
ISSN (versión digital)	2576-2370

Conferencia

Conferencia	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
País/Territorio	Estados Unidos
Ciudad	Los Angeles
Período	15/12/14 → 17/12/14

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10.1109/CDC.2014.7040223

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Zamora, E., & Yu, W. (2014). Ellipsoid method for Simultaneous Localization and Mapping of mobile robot. En 53rd IEEE Conference on Decision and Control,CDC 2014 (February ed., pp. 5334-5339). Artículo 7040223 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, N.º February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2014.7040223

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title = "Ellipsoid method for Simultaneous Localization and Mapping of mobile robot",

abstract = "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.",

author = "Erik Zamora and Wen Yu",

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doi = "10.1109/CDC.2014.7040223",

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series = "Proceedings of the IEEE Conference on Decision and Control",

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Zamora, E & Yu, W 2014, Ellipsoid method for Simultaneous Localization and Mapping of mobile robot. En 53rd IEEE Conference on Decision and Control,CDC 2014. February ed., 7040223, Proceedings of the IEEE Conference on Decision and Control, n.º February, vol. 2015-February, Institute of Electrical and Electronics Engineers Inc., pp. 5334-5339, 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014, Los Angeles, Estados Unidos, 15/12/14. https://doi.org/10.1109/CDC.2014.7040223

Ellipsoid method for Simultaneous Localization and Mapping of mobile robot. / Zamora, Erik; Yu, Wen.
53rd IEEE Conference on Decision and Control,CDC 2014. February. ed. Institute of Electrical and Electronics Engineers Inc., 2014. p. 5334-5339 7040223 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, N.º February).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - 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.

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Ellipsoid method for Simultaneous Localization and Mapping of mobile robot

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