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Position and Attitude Estimation Method Integrating Visual Odometer and GPS

The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where t...

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Detalles Bibliográficos
Autores principales: Yang, Yu, Shen, Qiang, Li, Jie, Deng, Zilong, Wang, Hanyu, Gao, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180583/
https://www.ncbi.nlm.nih.gov/pubmed/32283736
http://dx.doi.org/10.3390/s20072121
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author Yang, Yu
Shen, Qiang
Li, Jie
Deng, Zilong
Wang, Hanyu
Gao, Xiao
author_facet Yang, Yu
Shen, Qiang
Li, Jie
Deng, Zilong
Wang, Hanyu
Gao, Xiao
author_sort Yang, Yu
collection PubMed
description The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods.
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spelling pubmed-71805832020-05-01 Position and Attitude Estimation Method Integrating Visual Odometer and GPS Yang, Yu Shen, Qiang Li, Jie Deng, Zilong Wang, Hanyu Gao, Xiao Sensors (Basel) Article The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods. MDPI 2020-04-09 /pmc/articles/PMC7180583/ /pubmed/32283736 http://dx.doi.org/10.3390/s20072121 Text en © 2020 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
Yang, Yu
Shen, Qiang
Li, Jie
Deng, Zilong
Wang, Hanyu
Gao, Xiao
Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title_full Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title_fullStr Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title_full_unstemmed Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title_short Position and Attitude Estimation Method Integrating Visual Odometer and GPS
title_sort position and attitude estimation method integrating visual odometer and gps
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180583/
https://www.ncbi.nlm.nih.gov/pubmed/32283736
http://dx.doi.org/10.3390/s20072121
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