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Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System

Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology,...

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Detalles Bibliográficos
Autores principales: Zhao, Jiangying, Hu, Yongbiao, Tian, Mingrui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8272127/
https://www.ncbi.nlm.nih.gov/pubmed/34208917
http://dx.doi.org/10.3390/s21134478
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author Zhao, Jiangying
Hu, Yongbiao
Tian, Mingrui
author_facet Zhao, Jiangying
Hu, Yongbiao
Tian, Mingrui
author_sort Zhao, Jiangying
collection PubMed
description Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines.
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spelling pubmed-82721272021-07-11 Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System Zhao, Jiangying Hu, Yongbiao Tian, Mingrui Sensors (Basel) Article Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines. MDPI 2021-06-30 /pmc/articles/PMC8272127/ /pubmed/34208917 http://dx.doi.org/10.3390/s21134478 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Jiangying
Hu, Yongbiao
Tian, Mingrui
Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title_full Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title_fullStr Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title_full_unstemmed Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title_short Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System
title_sort pose estimation of excavator manipulator based on monocular vision marker system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8272127/
https://www.ncbi.nlm.nih.gov/pubmed/34208917
http://dx.doi.org/10.3390/s21134478
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