Conference paper

ILA Viorela S., POLOK Lukáš, SMRŽ Pavel, ŠOLONY Marek and ZEMČÍK Pavel. Incremental Cholesky Factorization for Least Squares Problems in Robotics. In: Proceedings of The 2013 IFAC Intelligent Autonomous Vehicles Symposium. Gold Coast: IEEE Computer Society, 2013, pp. 1-8. ISBN 978-3-902823-36-6. Available from: http://www.sciencedirect.com/science/article/pii/S1474667015349284
Publication language:english
Original title:Incremental Cholesky Factorization for Least Squares Problems in Robotics
Title (cs):Inkrementální Choleského faktorizace pro řešení problémů typu nejmenších čtverců pro robotické aplikace
Pages:1-8
Proceedings:Proceedings of The 2013 IFAC Intelligent Autonomous Vehicles Symposium
Conference:The 2013 IFAC Intelligent Autonomous Vehicles Symposium
Place:Gold Coast, AU
Year:2013
URL:http://www.sciencedirect.com/science/article/pii/S1474667015349284
ISBN:978-3-902823-36-6
Publisher:IEEE Computer Society
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Keywords
Robotics, Least squares problems, SLAM, Incremental solvers
Annotation
The paper proposes a novel efficient incremental solution to least squares problems, with focus on the use in robotic applications, especially the simultaneous location an mapping problem. The results are very good, the proposed method significantly outperforms all the major state of the art implementations.
Abstract
Online applications in robotics, computer vision, and computer graphics rely on eciently solving the associated nolinear systems every step. Iteratively solving the non-linear
system every step becomes very expensive if the size of the problem grows. This can be mitigated by incrementally updating the linear system and changing the linearization point only if needed. This paper proposes an incremental solution that adapts to the size of the updates while keeping the error of the estimation low. The implementation also differs form the existing ones in the way it exploits the block structure of such problems and offers efficient solutions to manipulate block matrices within incremental nonlinear solvers. In this work, in particular, we focus our effort on testing the method on simultaneous localization and mapping (SLAM) applications, but the applicability of the technique remains general. The experimental results show that our implementation outperforms the state of the art SLAM implementations on all tested datasets.
BibTeX:
@INPROCEEDINGS{
   author = {S. Viorela Ila and Luk{\'{a}}{\v{s}} Polok and Pavel
	Smr{\v{z}} and Marek {\v{S}}olony and Pavel
	Zem{\v{c}}{\'{i}}k},
   title = {Incremental Cholesky Factorization for Least Squares
	Problems in Robotics},
   pages = {1--8},
   booktitle = {Proceedings of The 2013 IFAC Intelligent Autonomous Vehicles
	Symposium},
   year = {2013},
   location = {Gold Coast, AU},
   publisher = {IEEE Computer Society},
   ISBN = {978-3-902823-36-6},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=10347}
}

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