Point-based Scan Matching by Differential Evolution

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86100121" target="_blank" >RIV/61989100:27240/16:86100121 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/INCoS.2016.62" target="_blank" >http://dx.doi.org/10.1109/INCoS.2016.62</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/INCoS.2016.62" target="_blank" >10.1109/INCoS.2016.62</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Point-based Scan Matching by Differential Evolution

Popis výsledku v původním jazyce

Nature-inspired metaheuristics have been applied in many different areas and have shown good results in comparison with traditional domain-specific optimization methods. In this work, we investigate the ability of a simple variant of differential evolution to solve 2D scan matching problem. It consists in finding an optimum affine transformation (rotation and translation) between two laser scans (2D pointclouds). Parameters of the affine transformation are in this approach determined by differential evolution. All steps of the proposed algorithm are data parallel and can be efficiently accelerated by massively parallel platforms including mobile graphical processing units. The proposed method was implemented and experimentally evaluated on a test data set. The obtained results show that it achieves a good accuracy and is a promising technique for real-world applications in mobile robotics.

Název v anglickém jazyce

Point-based Scan Matching by Differential Evolution

Popis výsledku anglicky

Nature-inspired metaheuristics have been applied in many different areas and have shown good results in comparison with traditional domain-specific optimization methods. In this work, we investigate the ability of a simple variant of differential evolution to solve 2D scan matching problem. It consists in finding an optimum affine transformation (rotation and translation) between two laser scans (2D pointclouds). Parameters of the affine transformation are in this approach determined by differential evolution. All steps of the proposed algorithm are data parallel and can be efficiently accelerated by massively parallel platforms including mobile graphical processing units. The proposed method was implemented and experimentally evaluated on a test data set. The obtained results show that it achieves a good accuracy and is a promising technique for real-world applications in mobile robotics.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Mnohoparadigmatické algoritmy dolování z dat založené na vyhledávání, fuzzy technologiích a bio-inspirovaných výpočtech</a><br>

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

8th International Conference on Intelligent Networking and Collaborative Systems (INCoS 2016) : proceedings papers

ISBN

978-1-5090-4123-7

ISSN

2470-9166

e-ISSN

—

Počet stran výsledku

7

Strana od-do

215-221

Název nakladatele

IEEE

Místo vydání

Vienna

Místo konání akce

Ostrava

Datum konání akce

7. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000386596100037