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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,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7729766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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