Efficient Implementation for Block Matrix Operations Nonlinear Least Squares Problems for Robotic Applications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F13%3APU106287" target="_blank" >RIV/00216305:26230/13:PU106287 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/6630883/?arnumber=6630883" target="_blank" >http://ieeexplore.ieee.org/document/6630883/?arnumber=6630883</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA.2013.6630883" target="_blank" >10.1109/ICRA.2013.6630883</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Efficient Implementation for Block Matrix Operations Nonlinear Least Squares Problems for Robotic Applications

Popis výsledku v původním jazyce

A large number of robotic, computer vision and computer graphics applications rely on efficiently solving the associated sparse linear system. Simultaneous localization and mapping (SLAM), structure from motion (SFM), non-rigid shape recovery, elastodynamic simulations, are only few examples in this direction. In general, those problems are non-linear and the solution can be approximated by incrementally solving a series of linearized problems. In some applications, the size of the systems might considerable affect the performance, especially when the sparsity is low. This paper exploits the block structure of such problems and offers efficient solutions to manipulate block matrices. In particular, we focus on testing the method on SLAM applications, but the applicability of the technique remains general.

Název v anglickém jazyce

Efficient Implementation for Block Matrix Operations Nonlinear Least Squares Problems for Robotic Applications

Popis výsledku anglicky

A large number of robotic, computer vision and computer graphics applications rely on efficiently solving the associated sparse linear system. Simultaneous localization and mapping (SLAM), structure from motion (SFM), non-rigid shape recovery, elastodynamic simulations, are only few examples in this direction. In general, those problems are non-linear and the solution can be approximated by incrementally solving a series of linearized problems. In some applications, the size of the systems might considerable affect the performance, especially when the sparsity is low. This paper exploits the block structure of such problems and offers efficient solutions to manipulate block matrices. In particular, we focus on testing the method on SLAM applications, but the applicability of the technique remains general.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 2013 IEEE International Conference on Robotics and Automation

ISBN

978-1-4673-5642-8

ISSN

—

e-ISSN

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Počet stran výsledku

8

Strana od-do

123-131

Název nakladatele

IEEE Computer Society

Místo vydání

Karlsruhe

Místo konání akce

Karlsruhe, Germany

Datum konání akce

6. 5. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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