Towards a consistent SLAM algorithm using B-splines to represent environments

Liu, M; Huang, S; Dissanayake, G; Kodagoda, S

Towards a consistent SLAM algorithm using B-splines to represent environments

Liu, M Huang, S

Dissanayake, G

Kodagoda, S

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Publication Type:: Conference Proceeding
Citation:: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings, 2010, pp. 2065 - 2070
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Liu, M	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.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings, 2010, pp. 2065 - 2070	en_US
dc.identifier.isbn	9781424466757	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16143
dc.description.abstract	This paper presents a statistically consistent SLAM algorithm where the environment is represented using a collection of B-Splines. The use of B-Splines allow environment to be represented without having to extract specific geometric features such as lines or points. Our previous work proposed a new observation model that enables raw measurements taken from a laser range finder to be transferred into relative position information between the control points of a B-Spline and the robot pose where the observation is made. One of the unresolved issues in the work was the estimation of the observation covariance, which is addressed through an analytical approach in this paper. As the uncertainty associated with the observation model is accurately defined and an optimization approach is used in the estimation process, the proposed SLAM algorithm can produce consistent estimates. Both simulation and experimental data are used for evaluation of the results. ©2010 IEEE.	en_US
dc.relation.ispartof	IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings	en_US
dc.relation.isbasedon	10.1109/IROS.2010.5649703	en_US
dc.title	Towards a consistent SLAM algorithm using B-splines to represent environments	en_US
dc.type	Conference Proceeding
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
dc.location.activity	Taipei, Taiwan	en_US
dc.location.activity	Taipei, TAIWAN
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

Abstract:

This paper presents a statistically consistent SLAM algorithm where the environment is represented using a collection of B-Splines. The use of B-Splines allow environment to be represented without having to extract specific geometric features such as lines or points. Our previous work proposed a new observation model that enables raw measurements taken from a laser range finder to be transferred into relative position information between the control points of a B-Spline and the robot pose where the observation is made. One of the unresolved issues in the work was the estimation of the observation covariance, which is addressed through an analytical approach in this paper. As the uncertainty associated with the observation model is accurately defined and an optimization approach is used in the estimation process, the proposed SLAM algorithm can produce consistent estimates. Both simulation and experimental data are used for evaluation of the results. ©2010 IEEE.

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http://hdl.handle.net/10453/16143