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A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles †
Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automate...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832443/ https://www.ncbi.nlm.nih.gov/pubmed/31627400 http://dx.doi.org/10.3390/s19204513 |
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author | Freimuth, Henk König, Markus |
author_facet | Freimuth, Henk König, Markus |
author_sort | Freimuth, Henk |
collection | PubMed |
description | Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automated creation of images and point cloud data of particular construction objects. The method extracts locations of objects that require inspection from Four Dimensional Building Information Modelling (4D-BIM). With this information at hand viable flight missions around the known structures of the construction site are computed. During flight, the UAV uses stereo cameras to detect and avoid any obstacles that are not known to the model, for example moving humans or machinery. The combination of pre-computed waypoint missions and reactive avoidance ensures deterministic routing from takeoff to landing and operational safety for humans and machines. During flight, an additional software component compares the captured point cloud data with the model data, enabling automatic per-object completion checking or reconstruction. The prototype is developed in the Robot Operating System (ROS) and evaluated in Software-In-The-Loop (SITL) simulations for the sake of being executable on real UAVs. |
format | Online Article Text |
id | pubmed-6832443 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68324432019-11-25 A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † Freimuth, Henk König, Markus Sensors (Basel) Article Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automated creation of images and point cloud data of particular construction objects. The method extracts locations of objects that require inspection from Four Dimensional Building Information Modelling (4D-BIM). With this information at hand viable flight missions around the known structures of the construction site are computed. During flight, the UAV uses stereo cameras to detect and avoid any obstacles that are not known to the model, for example moving humans or machinery. The combination of pre-computed waypoint missions and reactive avoidance ensures deterministic routing from takeoff to landing and operational safety for humans and machines. During flight, an additional software component compares the captured point cloud data with the model data, enabling automatic per-object completion checking or reconstruction. The prototype is developed in the Robot Operating System (ROS) and evaluated in Software-In-The-Loop (SITL) simulations for the sake of being executable on real UAVs. MDPI 2019-10-17 /pmc/articles/PMC6832443/ /pubmed/31627400 http://dx.doi.org/10.3390/s19204513 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Freimuth, Henk König, Markus A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title | A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title_full | A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title_fullStr | A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title_full_unstemmed | A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title_short | A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles † |
title_sort | framework for automated acquisition and processing of as-built data with autonomous unmanned aerial vehicles † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832443/ https://www.ncbi.nlm.nih.gov/pubmed/31627400 http://dx.doi.org/10.3390/s19204513 |
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