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Remotely piloted aircraft‐based automated vertical surface survey

Remotely Piloted Aircrafts (RPAs) are commonly used as a platform for collecting images which can be processed with Structure from Motion-Multi View Stereo (SfM-MVS) to generate 3D models. However, mobile applications for mapping planning are not designed for image acquisition of vertical surfaces,...

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Detalles Bibliográficos
Autores principales: Grohmann, Carlos H., Viana, Camila D., Garcia, Guilherme P.B., Albuquerque, Rafael W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803766/
https://www.ncbi.nlm.nih.gov/pubmed/36593760
http://dx.doi.org/10.1016/j.mex.2022.101982
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author Grohmann, Carlos H.
Viana, Camila D.
Garcia, Guilherme P.B.
Albuquerque, Rafael W.
author_facet Grohmann, Carlos H.
Viana, Camila D.
Garcia, Guilherme P.B.
Albuquerque, Rafael W.
author_sort Grohmann, Carlos H.
collection PubMed
description Remotely Piloted Aircrafts (RPAs) are commonly used as a platform for collecting images which can be processed with Structure from Motion-Multi View Stereo (SfM-MVS) to generate 3D models. However, mobile applications for mapping planning are not designed for image acquisition of vertical surfaces, such as quarry walls or large cliffs, leaving the user to a manual flight operation, which does not ensure optimal overlap between images. Here we describe a workflow, based on the Litchi App, for automated RPA missions designed to acquire images of vertical surfaces or structures. • An easy-to-follow 8 steps method to survey vertical surfaces using a Remotely Piloted Aircraft. • It can be applied to outcrops, quarry walls, high cliffs and virtually any other type of vertical surface. • The workflow is flexible and can be adapted to a variety of target configurations and user-defined parameters.
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spelling pubmed-98037662023-01-01 Remotely piloted aircraft‐based automated vertical surface survey Grohmann, Carlos H. Viana, Camila D. Garcia, Guilherme P.B. Albuquerque, Rafael W. MethodsX Method Article Remotely Piloted Aircrafts (RPAs) are commonly used as a platform for collecting images which can be processed with Structure from Motion-Multi View Stereo (SfM-MVS) to generate 3D models. However, mobile applications for mapping planning are not designed for image acquisition of vertical surfaces, such as quarry walls or large cliffs, leaving the user to a manual flight operation, which does not ensure optimal overlap between images. Here we describe a workflow, based on the Litchi App, for automated RPA missions designed to acquire images of vertical surfaces or structures. • An easy-to-follow 8 steps method to survey vertical surfaces using a Remotely Piloted Aircraft. • It can be applied to outcrops, quarry walls, high cliffs and virtually any other type of vertical surface. • The workflow is flexible and can be adapted to a variety of target configurations and user-defined parameters. Elsevier 2022-12-21 /pmc/articles/PMC9803766/ /pubmed/36593760 http://dx.doi.org/10.1016/j.mex.2022.101982 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Method Article
Grohmann, Carlos H.
Viana, Camila D.
Garcia, Guilherme P.B.
Albuquerque, Rafael W.
Remotely piloted aircraft‐based automated vertical surface survey
title Remotely piloted aircraft‐based automated vertical surface survey
title_full Remotely piloted aircraft‐based automated vertical surface survey
title_fullStr Remotely piloted aircraft‐based automated vertical surface survey
title_full_unstemmed Remotely piloted aircraft‐based automated vertical surface survey
title_short Remotely piloted aircraft‐based automated vertical surface survey
title_sort remotely piloted aircraft‐based automated vertical surface survey
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803766/
https://www.ncbi.nlm.nih.gov/pubmed/36593760
http://dx.doi.org/10.1016/j.mex.2022.101982
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