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A multilevel relaxation algorithm for simultaneous localisation and mapping
University of Bremen. (Bremen Institute of Safe Systems)
NamaTec AB. (Sweden)
Örebro University, Department of Technology. (Learning Systems Lab)
2005 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 21, no 2, p. 196-207Article in journal (Refereed) Published
Abstract [en]

This paper addresses the problem of simultaneous localisation and mapping (SLAM) by a mobile robot. An incremental SLAM algorithm is introduced that is derived from multigrid methods used for solving partial differential equations. The approach improves on the performance of previous relaxation methods for robot mapping because it optimizes the map at multiple levels of resolution. The resulting algorithm has an update time that is linear in the number of estimated features for typical indoor environments, even when closing very large loops, and offers advantages in handling non-linearities compared to other SLAM algorithms. Experimental comparisons with alternative algorithms using two well-known data sets and mapping results on a real robot are also presented

Place, publisher, year, edition, pages
2005. Vol. 21, no 2, p. 196-207
Keywords [en]
Termsómobile robot navigation, SLAM, metrictopological maps, Gauss-Seidel relaxation, Galerkin multigrid
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-3497DOI: 10.1109/TRO.2004.839220OAI: oai:DiVA.org:oru-3497DiVA, id: diva2:137794
Available from: 2007-07-22 Created: 2007-07-22 Last updated: 2017-12-14Bibliographically approved

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