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Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera

Using a standalone camera for pose estimation has been quite a standard task. However, the point correspondence-based algorithms require at least four feature points in the field of view. This paper considers the situation that there are only two feature points. Focusing on the attitude estimation,...

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Detalles Bibliográficos
Autores principales: Zheng, Lingxiao, Zhan, Xingqun, Zhang, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729766/
https://www.ncbi.nlm.nih.gov/pubmed/33255946
http://dx.doi.org/10.3390/s20236752
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author Zheng, Lingxiao
Zhan, Xingqun
Zhang, Xin
author_facet Zheng, Lingxiao
Zhan, Xingqun
Zhang, Xin
author_sort Zheng, Lingxiao
collection PubMed
description Using a standalone camera for pose estimation has been quite a standard task. However, the point correspondence-based algorithms require at least four feature points in the field of view. This paper considers the situation that there are only two feature points. Focusing on the attitude estimation, we propose to fuse a camera with low-cost inertial sensors based on a nonlinear complementary filter design. An implicit geometry measurement model is derived using two feature points in an image. This geometry measurement is fused with the angle rate measurement and vector measurement from inertial sensors using the proposed nonlinear complementary filter with only two parameters to be adjusted. The proposed nonlinear complementary filter is posed directly on the special orthogonal group SO(3). Based on the theory of nonlinear system stability analysis, the proposed filter ensures locally asymptotic stability. A quaternion-based discrete implementation of the filter is also given in this paper for computational efficiency. The proposed algorithm is validated using a smartphone with built-in inertial sensors and a rear camera. The experimental results indicate that the proposed algorithm outperforms all the compared counterparts in estimated accuracy and provides competitive computational complexity.
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spelling pubmed-77297662020-12-12 Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera Zheng, Lingxiao Zhan, Xingqun Zhang, Xin Sensors (Basel) Article Using a standalone camera for pose estimation has been quite a standard task. However, the point correspondence-based algorithms require at least four feature points in the field of view. This paper considers the situation that there are only two feature points. Focusing on the attitude estimation, we propose to fuse a camera with low-cost inertial sensors based on a nonlinear complementary filter design. An implicit geometry measurement model is derived using two feature points in an image. This geometry measurement is fused with the angle rate measurement and vector measurement from inertial sensors using the proposed nonlinear complementary filter with only two parameters to be adjusted. The proposed nonlinear complementary filter is posed directly on the special orthogonal group SO(3). Based on the theory of nonlinear system stability analysis, the proposed filter ensures locally asymptotic stability. A quaternion-based discrete implementation of the filter is also given in this paper for computational efficiency. The proposed algorithm is validated using a smartphone with built-in inertial sensors and a rear camera. The experimental results indicate that the proposed algorithm outperforms all the compared counterparts in estimated accuracy and provides competitive computational complexity. MDPI 2020-11-26 /pmc/articles/PMC7729766/ /pubmed/33255946 http://dx.doi.org/10.3390/s20236752 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
Zheng, Lingxiao
Zhan, Xingqun
Zhang, Xin
Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title_full Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title_fullStr Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title_full_unstemmed Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title_short Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera
title_sort nonlinear complementary filter for attitude estimation by fusing inertial sensors and a camera
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729766/
https://www.ncbi.nlm.nih.gov/pubmed/33255946
http://dx.doi.org/10.3390/s20236752
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