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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/439C63H
Repositorysid.inpe.br/mtc-m21c/2020/09.17.12.16   (restricted access)
Last Update2020:09.17.12.16.33 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2020/09.17.12.16.33
Metadata Last Update2022:01.04.01.35.24 (UTC) administrator
Secondary KeyINPE--PRE/
ISBN978-303053668-8
ISSN21954356
Citation KeyPenhaNetoCampShig:2020:UAAuNa
TitleUAV autonomous navigation by image processing with uncertainty trajectory estimation
Year2020
Access Date2024, May 17
Secondary TypePRE CI
Number of Files1
Size2261 KiB
2. Context
Author1 Penha Neto, Gerson da
2 Campos Velho, Haroldo Fraga de
3 Shiguemori, Elcio Hideiti
Resume Identifier1
2 8JMKD3MGP5W/3C9JHC3
Group1 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
2 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto de Estudos Avançados (IEAv)
Author e-Mail Address1 gerson.penha@inpe.br
2 haroldo.camposvelho@inpe.br
3 elcio@ieav.cta.br
EditorCursi, J. E. S.
Conference NameInternational Symposium on Uncertainty Quantification and Stochastic Modelling, 5
Conference LocationRouen, France
Date29 jun. - 03 jul.
PublisherSpringer
Pages211-221
Book TitleProceedings
History (UTC)2020-09-17 12:17:27 :: simone -> administrator :: 2020
2022-01-04 01:35:24 :: administrator -> simone :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsUnmanned Aerial Vehicles
Autonomous navigation
Image processing
Self-configuring neural network
Uncertainty quantification
AbstractUnmanned Aerial Vehicles (UAV) is a technology under strong development, with application on several fields. For the UAV autonomous navigation, a standard scheme is to use signal from a Global Navigation System by Satellite (GNSS) onboard. However, such signal can suffer natural or human interference. Our approach applies image processing procedure for the UAV positioning: image edge extraction and correlation between drone image and georeferenced satellite image. A data fusion is also applied, for combining the inertial sensor data and positioning by image. The data fusion is performed by using neural network. The output from the data fusion neural network is the correction for the UAV trajectory. Here, the variance of the trajectory error is also predicted to quantify the uncertainty.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > UAV autonomous navigation...
Arrangement 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > UAV autonomous navigation...
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4. Conditions of access and use
Languageen
Target Filepenha neto_uav.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3F2PHGS
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.40 4
sid.inpe.br/bibdigital/2013/10.12.22.16 3
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
NotesLecture Notes in Mechanical Engineering
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition format label lineage mark mirrorrepository nextedition numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume
7. Description control
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