Title:
Exploiting Locality by Nested Dissection For Square Root Smoothing and Mapping

dc.contributor.author Krauthausen, Peter
dc.contributor.author Dellaert, Frank
dc.contributor.author Kipp, Alexander
dc.date.accessioned 2006-03-17T14:37:48Z
dc.date.available 2006-03-17T14:37:48Z
dc.date.issued 2005
dc.description.abstract The problem of creating a map given only the erroneous odometry and feature measurements and locating the own position in this environment is known in the literature as the Simultaneous Localization and Mapping (SLAM) problem. In this paper we investigate how a Nested Dissection Ordering scheme can improve the the performance of a recently proposed Square Root Information Smoothing (SRIS) approach. As the SRIS does perform smoothing rather than filtering the SLAM problem becomes the Smoothing and Mapping problem (SAM). The computational complexity of the SRIS solution is dominated by the cost of transforming a matrix of all measurements into a square root form through factorization. The factorization of a fully dense measurement matrix has a cubic complexity in the worst case. We show that the computational complexity for the factorization of typical measurement matrices occurring in the SAM problem can be bound tighter under reasonable assumptions. Our work is motivated both from a numerical/linear algebra standpoint as well as by submaps used in EKF solutions to SLAM. en
dc.format.extent 801538 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/8363
dc.language.iso en_US en
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries GVU Technical Report;GIT-GVU-05-26 en
dc.subject Robotics en
dc.subject Simultaneous mapping and localization en
dc.subject Applied math en
dc.subject Graph theory en
dc.title Exploiting Locality by Nested Dissection For Square Root Smoothing and Mapping en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.author Dellaert, Frank
local.contributor.corporatename GVU Center
local.relation.ispartofseries GVU Technical Report Series
relation.isAuthorOfPublication dac80074-d9d8-4358-b6eb-397d95bdc868
relation.isOrgUnitOfPublication d5666874-cf8d-45f6-8017-3781c955500f
relation.isSeriesOfPublication a13d1649-8f8b-4a59-9dec-d602fa26bc32
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