Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones
A multimodal sensory array to accurately position aerial multicopter drones with respect to pipes has been studied, and a solution exploiting both LiDAR and vision sensors has been proposed. Several challenges, including detection of pipes and other cylindrical elements in sensor space and validatio...
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2018-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/2758021 |
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doaj-a9d46c0d74a349cb840d117902df09082020-11-24T20:50:48ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/27580212758021Detection and Positioning of Pipes and Columns with Autonomous Multicopter DronesEdmundo Guerra0Rodrigo Munguía1Yolanda Bolea2Antoni Grau3Department of Automatic Control, Technical University of Catalonia UPC, Barcelona 08034, SpainDepartment of Computer Science, CUCEI, University of Guadalajara, Guadalajara 44430, MexicoDepartment of Automatic Control, Technical University of Catalonia UPC, Barcelona 08034, SpainDepartment of Automatic Control, Technical University of Catalonia UPC, Barcelona 08034, SpainA multimodal sensory array to accurately position aerial multicopter drones with respect to pipes has been studied, and a solution exploiting both LiDAR and vision sensors has been proposed. Several challenges, including detection of pipes and other cylindrical elements in sensor space and validation of the elements detected, have been studied. A probabilistic parametric method has been applied to segment and position cylinders with LIDAR, while several vision-based techniques have been tested to find the contours of the pipe, combined with conic estimation cylinder pose recovery. Multiple solutions have been studied and analyzed, evaluating their results. This allowed proposing an approach that combines both LiDAR and vision to produce robust and accurate pipe detection. This combined solution is validated with real experimental data.http://dx.doi.org/10.1155/2018/2758021 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Edmundo Guerra Rodrigo Munguía Yolanda Bolea Antoni Grau |
spellingShingle |
Edmundo Guerra Rodrigo Munguía Yolanda Bolea Antoni Grau Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones Mathematical Problems in Engineering |
author_facet |
Edmundo Guerra Rodrigo Munguía Yolanda Bolea Antoni Grau |
author_sort |
Edmundo Guerra |
title |
Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones |
title_short |
Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones |
title_full |
Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones |
title_fullStr |
Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones |
title_full_unstemmed |
Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones |
title_sort |
detection and positioning of pipes and columns with autonomous multicopter drones |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2018-01-01 |
description |
A multimodal sensory array to accurately position aerial multicopter drones with respect to pipes has been studied, and a solution exploiting both LiDAR and vision sensors has been proposed. Several challenges, including detection of pipes and other cylindrical elements in sensor space and validation of the elements detected, have been studied. A probabilistic parametric method has been applied to segment and position cylinders with LIDAR, while several vision-based techniques have been tested to find the contours of the pipe, combined with conic estimation cylinder pose recovery. Multiple solutions have been studied and analyzed, evaluating their results. This allowed proposing an approach that combines both LiDAR and vision to produce robust and accurate pipe detection. This combined solution is validated with real experimental data. |
url |
http://dx.doi.org/10.1155/2018/2758021 |
work_keys_str_mv |
AT edmundoguerra detectionandpositioningofpipesandcolumnswithautonomousmulticopterdrones AT rodrigomunguia detectionandpositioningofpipesandcolumnswithautonomousmulticopterdrones AT yolandabolea detectionandpositioningofpipesandcolumnswithautonomousmulticopterdrones AT antonigrau detectionandpositioningofpipesandcolumnswithautonomousmulticopterdrones |
_version_ |
1716803591521435648 |