Localization Fusion for Aerial Vehicles in Partially GNSS Denied Environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00336150" target="_blank" >RIV/68407700:21230/19:00336150 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-14984-0_20" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-14984-0_20</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Localization Fusion for Aerial Vehicles in Partially GNSS Denied Environments

Popis výsledku v původním jazyce

In this paper, we report on early results of the experimental deployment of localization techniques for a multi-rotor Micro Aerial Vehicle (MAV). In particular, we focus on deployment scenarios where the Global Navigation Satellite System (GNSS) does not provide a reliable signal, and thus it is not desirable to rely solely on the GNSS. Therefore, we consider recent advancements in the visual localization, and we employ an onboard RGB-D camera to develop a robust and reliable solution for the MAV localization in partially GNSS denied operational environments. We consider a localization method based on Kalman filter for data fusion of the vision-based localization with the signal from the GNSS. Based on the reported experimental results, the proposed solution supports the localization of the MAV for the temporarily unavailable GNSS, but also improves the position estimation provided by the incremental vision-based localization system while it can run using onboard computational resources of the small vehicle.

Název v anglickém jazyce

Localization Fusion for Aerial Vehicles in Partially GNSS Denied Environments

Popis výsledku anglicky

In this paper, we report on early results of the experimental deployment of localization techniques for a multi-rotor Micro Aerial Vehicle (MAV). In particular, we focus on deployment scenarios where the Global Navigation Satellite System (GNSS) does not provide a reliable signal, and thus it is not desirable to rely solely on the GNSS. Therefore, we consider recent advancements in the visual localization, and we employ an onboard RGB-D camera to develop a robust and reliable solution for the MAV localization in partially GNSS denied operational environments. We consider a localization method based on Kalman filter for data fusion of the vision-based localization with the signal from the GNSS. Based on the reported experimental results, the proposed solution supports the localization of the MAV for the temporarily unavailable GNSS, but also improves the position estimation provided by the incremental vision-based localization system while it can run using onboard computational resources of the small vehicle.

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

<a href="/cs/project/TH03010362" target="_blank" >TH03010362: Hybridní navigační systém pro autonomní prostředky v prostředí se sníženou kvalitou GNSS signálu</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Modelling and Simulation for Autonomous Systems

ISBN

978-3-030-14983-3

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

12

Strana od-do

251-262

Název nakladatele

Springer

Místo vydání

Basel

Místo konání akce

Praha

Datum konání akce

17. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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