Probabilistic Self-Localization and Mapping - An Asynchronous Multirate Approach

One of the main contributions of this article is related to the multirate asynchronous filtering approach for the SLAM problem based on PFs. Previous multirate filter contributions are mainly for linear systems. A Kalman filter is applied for linear quadratic regulator (LQG) control, while in a Kalm...

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Bibliographic Details
Published in:IEEE robotics & automation magazine 2008-06, Vol.15 (2), p.77-88
Main Authors: Armesto, L., Ippoliti, G., Longhi, S., Tornero, J.
Format: Article
Language:English
Subjects:
Algorithms
Automation
Filtering
Filters
Filtration
Fittings
Fuses
Kalman filters
Least squares approximation
Position (location)
Robot sensing systems
Robots
Robustness
Sampling methods
Sensor fusion
Simultaneous localization and mapping
State estimation
Studies
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Summary:One of the main contributions of this article is related to the multirate asynchronous filtering approach for the SLAM problem based on PFs. Previous multirate filter contributions are mainly for linear systems. A Kalman filter is applied for linear quadratic regulator (LQG) control, while in a Kalman filter is developed using lifting techniques. In this article, significant improvements for robot pose estimation are obtained when introducing multirate techniques to FastSLAM. In particular, it is shown that multirate fusion aims to provide more accurate results in loop-closing problems in SLAM (localization and map building problems with closed paths). Additionally, in this article a pose estimation algorithm based on least squares (LS) fitting of line features is proposed. Since the complexity of LS fitting is linear to the number of features, this implies a low computational cost than other techniques. Therefore, methods based on PFs such as MCL and FastSLAM that require a large number of particles may benefit from this fact. In particular, this provides an accurate approximation of the posterior PDF for FastSLAM 2.0.
ISSN:1070-9932
1558-223X
DOI:10.1109/M-RA.2007.907355