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A Robust Planar Marker-Based Visual SLAM
Many visual SLAM systems are generally solved using natural landmarks or optical flow. However, due to textureless areas, illumination change or motion blur, they often acquire poor camera poses or even fail to track. Additionally, they cannot obtain camera poses with a metric scale in the monocular...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865496/ https://www.ncbi.nlm.nih.gov/pubmed/36679714 http://dx.doi.org/10.3390/s23020917 |
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author | Wang, Zhoubo Zhang, Zhenhai Zhu, Wei Hu, Xuehai Deng, Hongbin He, Guang Kang, Xiao |
author_facet | Wang, Zhoubo Zhang, Zhenhai Zhu, Wei Hu, Xuehai Deng, Hongbin He, Guang Kang, Xiao |
author_sort | Wang, Zhoubo |
collection | PubMed |
description | Many visual SLAM systems are generally solved using natural landmarks or optical flow. However, due to textureless areas, illumination change or motion blur, they often acquire poor camera poses or even fail to track. Additionally, they cannot obtain camera poses with a metric scale in the monocular case. In some cases (such as when calibrating the extrinsic parameters of camera-IMU), we prefer to sacrifice the flexibility of such methods to improve accuracy and robustness by using artificial landmarks. This paper proposes enhancements to the traditional SPM-SLAM, which is a system that aims to build a map of markers and simultaneously localize the camera pose. By placing the markers in the surrounding environment, the system can run stably and obtain accurate camera poses. To improve robustness and accuracy in the case of rotational movements, we improve the initialization, keyframes insertion and relocalization. Additionally, we propose a novel method to estimate marker poses from a set of images to solve the problem of planar-marker pose ambiguity. Compared with the state-of-art, the experiments show that our system achieves better accuracy in most public sequences and is more robust than SPM-SLAM under rotational movements. Finally, the open-source code is publicly available and can be found at GitHub. |
format | Online Article Text |
id | pubmed-9865496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98654962023-01-22 A Robust Planar Marker-Based Visual SLAM Wang, Zhoubo Zhang, Zhenhai Zhu, Wei Hu, Xuehai Deng, Hongbin He, Guang Kang, Xiao Sensors (Basel) Article Many visual SLAM systems are generally solved using natural landmarks or optical flow. However, due to textureless areas, illumination change or motion blur, they often acquire poor camera poses or even fail to track. Additionally, they cannot obtain camera poses with a metric scale in the monocular case. In some cases (such as when calibrating the extrinsic parameters of camera-IMU), we prefer to sacrifice the flexibility of such methods to improve accuracy and robustness by using artificial landmarks. This paper proposes enhancements to the traditional SPM-SLAM, which is a system that aims to build a map of markers and simultaneously localize the camera pose. By placing the markers in the surrounding environment, the system can run stably and obtain accurate camera poses. To improve robustness and accuracy in the case of rotational movements, we improve the initialization, keyframes insertion and relocalization. Additionally, we propose a novel method to estimate marker poses from a set of images to solve the problem of planar-marker pose ambiguity. Compared with the state-of-art, the experiments show that our system achieves better accuracy in most public sequences and is more robust than SPM-SLAM under rotational movements. Finally, the open-source code is publicly available and can be found at GitHub. MDPI 2023-01-13 /pmc/articles/PMC9865496/ /pubmed/36679714 http://dx.doi.org/10.3390/s23020917 Text en © 2023 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 Wang, Zhoubo Zhang, Zhenhai Zhu, Wei Hu, Xuehai Deng, Hongbin He, Guang Kang, Xiao A Robust Planar Marker-Based Visual SLAM |
title | A Robust Planar Marker-Based Visual SLAM |
title_full | A Robust Planar Marker-Based Visual SLAM |
title_fullStr | A Robust Planar Marker-Based Visual SLAM |
title_full_unstemmed | A Robust Planar Marker-Based Visual SLAM |
title_short | A Robust Planar Marker-Based Visual SLAM |
title_sort | robust planar marker-based visual slam |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865496/ https://www.ncbi.nlm.nih.gov/pubmed/36679714 http://dx.doi.org/10.3390/s23020917 |
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