Implementation issues and experimental evaluation of D-SLAM

Wang, Z; Huang, S; Dissanayake, G

Implementation issues and experimental evaluation of D-SLAM

Wang, Z Huang, S

Dissanayake, G

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Publication Type:: Chapter
Citation:: 2006, 25 pp. 155 - 166
Issue Date:: 2006-01-01

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Field	Value	Language
dc.contributor.author	Wang, Z	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2006-01-01	en_US
dc.identifier.citation	2006, 25 pp. 155 - 166	en_US
dc.identifier.isbn	3540334521	en_US
dc.identifier.isbn	9783540334521	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11651
dc.description.abstract	© Springer-Verlag Berlin Heidelberg 2006. D-SLAM algorithm first described in [1.] allows SLAM to be decoupled into solving a non-linear static estimation problem for mapping and a three-dimensional estimation problem for localization. This paper presents a new version of the D-SLAM algorithm that uses an absolute map instead of a relative map as presented in [1.]. One of the significant advantages of D-SLAM algorithm is its O (N) computational cost where N is the total number of features (landmarks). The theoretical foundations of D-SLAM together with implementation issues including data association, state recovery, and computational complexity are addressed in detail. Evaluation of the D-SLAM algorithm is provided using both real experimental data and simulations.	en_US
dc.relation.isbasedon	10.1007/978-3-540-33453-8_14	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Implementation issues and experimental evaluation of D-SLAM	en_US
dc.type	Chapter
utslib.citation.volume	25	en_US
utslib.for	091007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)	en_US
utslib.for	090602 Control Systems, Robotics and Automation	en_US
utslib.for	091303 Autonomous Vehicles	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	25	en_US

Abstract:

© Springer-Verlag Berlin Heidelberg 2006. D-SLAM algorithm first described in [1.] allows SLAM to be decoupled into solving a non-linear static estimation problem for mapping and a three-dimensional estimation problem for localization. This paper presents a new version of the D-SLAM algorithm that uses an absolute map instead of a relative map as presented in [1.]. One of the significant advantages of D-SLAM algorithm is its O (N) computational cost where N is the total number of features (landmarks). The theoretical foundations of D-SLAM together with implementation issues including data association, state recovery, and computational complexity are addressed in detail. Evaluation of the D-SLAM algorithm is provided using both real experimental data and simulations.

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http://hdl.handle.net/10453/11651