Ellipsoid SLAM: a novel set membership method for simultaneous localization and mapping

Wen Yu; Erik Zamora; Alberto Soria

doi:10.1007/s10514-015-9447-y

Ellipsoid SLAM: a novel set membership method for simultaneous localization and mapping

Wen Yu, Erik Zamora, Alberto Soria

Unidad Profesional Interdisciplinaria de Ingeniería y Tecnologías Avanzadas (UPIITA)

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

Abstract

The extended Kalman filter (EKF) simultaneous localization and mapping (SLAM) requires the uncertainty to be Gaussian noise. This assumption can be relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and online problems. In this paper, we use ellipsoid algorithm for solving SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAMs, in noise condition, online realization, and large-scale problem. By bounded ellipsoid technique, we analyze the convergence and stability of the ellipsoid SLAM. Simulation and experimental results show that the proposed ellipsoid SLAM is effective for online and large-scale problems such as Victoria Park dataset.

Original language	English
Pages (from-to)	125-137
Number of pages	13
Journal	Autonomous Robots
Volume	40
Issue number	1
DOIs	https://doi.org/10.1007/s10514-015-9447-y
State	Published - 1 Jan 2016

Keywords

Convergence
Ellipsoid
SLAM
Set membership
Stability

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10.1007/s10514-015-9447-y

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title = "Ellipsoid SLAM: a novel set membership method for simultaneous localization and mapping",

abstract = "The extended Kalman filter (EKF) simultaneous localization and mapping (SLAM) requires the uncertainty to be Gaussian noise. This assumption can be relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and online problems. In this paper, we use ellipsoid algorithm for solving SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAMs, in noise condition, online realization, and large-scale problem. By bounded ellipsoid technique, we analyze the convergence and stability of the ellipsoid SLAM. Simulation and experimental results show that the proposed ellipsoid SLAM is effective for online and large-scale problems such as Victoria Park dataset.",

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author = "Wen Yu and Erik Zamora and Alberto Soria",

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AU - Yu, Wen

AU - Zamora, Erik

AU - Soria, Alberto

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N2 - The extended Kalman filter (EKF) simultaneous localization and mapping (SLAM) requires the uncertainty to be Gaussian noise. This assumption can be relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and online problems. In this paper, we use ellipsoid algorithm for solving SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAMs, in noise condition, online realization, and large-scale problem. By bounded ellipsoid technique, we analyze the convergence and stability of the ellipsoid SLAM. Simulation and experimental results show that the proposed ellipsoid SLAM is effective for online and large-scale problems such as Victoria Park dataset.

AB - The extended Kalman filter (EKF) simultaneous localization and mapping (SLAM) requires the uncertainty to be Gaussian noise. This assumption can be relaxed to bounded noise by the set membership SLAM. However, the published set membership SLAMs are not suitable for large-scale and online problems. In this paper, we use ellipsoid algorithm for solving SLAM problem. The proposed ellipsoid SLAM has advantages over EKF SLAM and the other set membership SLAMs, in noise condition, online realization, and large-scale problem. By bounded ellipsoid technique, we analyze the convergence and stability of the ellipsoid SLAM. Simulation and experimental results show that the proposed ellipsoid SLAM is effective for online and large-scale problems such as Victoria Park dataset.

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KW - Stability

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Ellipsoid SLAM: a novel set membership method for simultaneous localization and mapping

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Keywords

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