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Simultaneous localization and map building using natural features and absolute information

This work presents real time implementation algorithms of Simultaneous Localization and Map Building (SLAM) with emphasis to outdoor land vehicle applications in large environments. It presents the problematic of outdoors navigation in areas with combination of feature and featureless regions. The a...

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Bibliographic Details
Published in:Robotics and autonomous systems 2002-08, Vol.40 (2), p.79-90
Main Authors: Guivant, José E., Masson, Favio R., Nebot, Eduardo M.
Format: Article
Language:English
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Summary:This work presents real time implementation algorithms of Simultaneous Localization and Map Building (SLAM) with emphasis to outdoor land vehicle applications in large environments. It presents the problematic of outdoors navigation in areas with combination of feature and featureless regions. The aspect of feature detection and validation is investigated to reliably detect the predominant features in the environment. Aided SLAM algorithms are presented that incorporate absolute information in a consistent manner. The SLAM implementation uses the compressed filter algorithm to maintain the map with a cost proportional to number of landmarks in the local area. The information gathered in the local area requires a full SLAM update when the vehicle leaves the local area. Algorithms to reduce the full update computational cost are also presented. Finally, experimental results obtained with a standard vehicle running in unstructured outdoor environment are presented.
ISSN:0921-8890
1872-793X
DOI:10.1016/S0921-8890(02)00233-6