Model-based analysis of multi-UAV path planning for surveying postdisaster building damage
Descripción del Articulo
This study was partly funded by the Japan Society for the Promotion of Science (JSPS) Kakenhi Program (17H06108 and 21H05001); the Core Research Cluster of Disaster Science; the Tough Cyberphysical AI Research Center at Tohoku University, and the National Program for Scientic Research and Advanced S...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2021 |
| Institución: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/3026 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/3026 https://doi.org/10.1038/s41598-021-97804-4 |
| Nivel de acceso: | acceso abierto |
| Materia: | remote sensing techniques building damage https://purl.org/pe-repo/ocde/ford#2.07.06 |
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Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| title |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| spellingShingle |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage Nagasawa R. remote sensing techniques building damage https://purl.org/pe-repo/ocde/ford#2.07.06 |
| title_short |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| title_full |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| title_fullStr |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| title_full_unstemmed |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| title_sort |
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage |
| author |
Nagasawa R. |
| author_facet |
Nagasawa R. Mas E. Moya L. Koshimura S. |
| author_role |
author |
| author2 |
Mas E. Moya L. Koshimura S. |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Nagasawa R. Mas E. Moya L. Koshimura S. |
| dc.subject.none.fl_str_mv |
remote sensing techniques |
| topic |
remote sensing techniques building damage https://purl.org/pe-repo/ocde/ford#2.07.06 |
| dc.subject.es_PE.fl_str_mv |
building damage |
| dc.subject.ocde.none.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#2.07.06 |
| description |
This study was partly funded by the Japan Society for the Promotion of Science (JSPS) Kakenhi Program (17H06108 and 21H05001); the Core Research Cluster of Disaster Science; the Tough Cyberphysical AI Research Center at Tohoku University, and the National Program for Scientic Research and Advanced Studies (PROCIEN-CIA/CONCYTEC - PERU) [contract number 038-2019 FONDECYT-BM-INC-INV]. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.issued.fl_str_mv |
2021 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/3026 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1038/s41598-021-97804-4 |
| dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85115412318 |
| url |
https://hdl.handle.net/20.500.12390/3026 https://doi.org/10.1038/s41598-021-97804-4 |
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2-s2.0-85115412318 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartof.none.fl_str_mv |
Scientific Reports |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.uri.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
| rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.publisher.none.fl_str_mv |
Nature Research |
| publisher.none.fl_str_mv |
Nature Research |
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reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
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Consejo Nacional de Ciencia Tecnología e Innovación |
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CONCYTEC |
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CONCYTEC |
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CONCYTEC-Institucional |
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CONCYTEC-Institucional |
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Repositorio Institucional CONCYTEC |
| repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
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1844883036944990208 |
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Publicationrp08662600rp05687600rp05688600rp05690600Nagasawa R.Mas E.Moya L.Koshimura S.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2021https://hdl.handle.net/20.500.12390/3026https://doi.org/10.1038/s41598-021-97804-42-s2.0-85115412318This study was partly funded by the Japan Society for the Promotion of Science (JSPS) Kakenhi Program (17H06108 and 21H05001); the Core Research Cluster of Disaster Science; the Tough Cyberphysical AI Research Center at Tohoku University, and the National Program for Scientic Research and Advanced Studies (PROCIEN-CIA/CONCYTEC - PERU) [contract number 038-2019 FONDECYT-BM-INC-INV].Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In particular, building damage should be assessed to account for possible casualties, and displaced populations, to estimate long-term shelter capacities, and to assess the damage to services that depend on essential infrastructure (e.g. hospitals, schools, etc.). Remote sensing techniques, including satellite imagery, can be used to gathering such information so that the overall damage can be assessed. However, specific points of interest among the damaged buildings need higher resolution images and detailed information to assess the damage situation. These areas can be further assessed through unmanned aerial vehicles and 3D model reconstruction. This paper presents a multi-UAV coverage path planning method for the 3D reconstruction of postdisaster damaged buildings. The methodology has been implemented in NetLogo3D, a multi-agent model environment, and tested in a virtual built environment in Unity3D. The proposed method generates camera location points surrounding targeted damaged buildings. These camera location points are filtered to avoid collision and then sorted using the K-means or the Fuzzy C-means methods. After clustering camera location points and allocating these to each UAV unit, a route optimization process is conducted as a multiple traveling salesman problem. Final corrections are made to paths to avoid obstacles and give a resulting path for each UAV that balances the flight distance and time. The paper presents the details of the model and methodologies, and an examination of the texture resolution obtained from the proposed method and the conventional overhead flight with the nadir-looking method used in 3D mappings. The algorithm outperforms the conventional method in terms of the quality of the generated 3D model. © 2021, The Author(s).Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengNature ResearchScientific Reportsinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/remote sensing techniquesbuilding damage-1https://purl.org/pe-repo/ocde/ford#2.07.06-1Model-based analysis of multi-UAV path planning for surveying postdisaster building damageinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/3026oai:repositorio.concytec.gob.pe:20.500.12390/30262024-05-30 16:13:15.361https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d9a71691-2581-492b-b8a2-ab0e9fc1d686"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Model-based analysis of multi-UAV path planning for surveying postdisaster building damage</Title> <PublishedIn> <Publication> <Title>Scientific Reports</Title> </Publication> </PublishedIn> <PublicationDate>2021</PublicationDate> <DOI>https://doi.org/10.1038/s41598-021-97804-4</DOI> <SCP-Number>2-s2.0-85115412318</SCP-Number> <Authors> <Author> <DisplayName>Nagasawa R.</DisplayName> <Person id="rp08662" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Mas E.</DisplayName> <Person id="rp05687" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Moya L.</DisplayName> <Person id="rp05688" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Koshimura S.</DisplayName> <Person id="rp05690" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Nature Research</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Keyword>remote sensing techniques</Keyword> <Keyword>building damage</Keyword> <Abstract>Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In particular, building damage should be assessed to account for possible casualties, and displaced populations, to estimate long-term shelter capacities, and to assess the damage to services that depend on essential infrastructure (e.g. hospitals, schools, etc.). Remote sensing techniques, including satellite imagery, can be used to gathering such information so that the overall damage can be assessed. However, specific points of interest among the damaged buildings need higher resolution images and detailed information to assess the damage situation. These areas can be further assessed through unmanned aerial vehicles and 3D model reconstruction. This paper presents a multi-UAV coverage path planning method for the 3D reconstruction of postdisaster damaged buildings. The methodology has been implemented in NetLogo3D, a multi-agent model environment, and tested in a virtual built environment in Unity3D. The proposed method generates camera location points surrounding targeted damaged buildings. These camera location points are filtered to avoid collision and then sorted using the K-means or the Fuzzy C-means methods. After clustering camera location points and allocating these to each UAV unit, a route optimization process is conducted as a multiple traveling salesman problem. Final corrections are made to paths to avoid obstacles and give a resulting path for each UAV that balances the flight distance and time. The paper presents the details of the model and methodologies, and an examination of the texture resolution obtained from the proposed method and the conventional overhead flight with the nadir-looking method used in 3D mappings. The algorithm outperforms the conventional method in terms of the quality of the generated 3D model. © 2021, The Author(s).</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
| score |
13.304014 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
