Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Zhoubo, Zhang, Zhenhai, Zhu, Wei, Hu, Xuehai, Deng, Hongbin, He, Guang, Kang, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1784875852526256128
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
work_keys_str_mv AT wangzhoubo arobustplanarmarkerbasedvisualslam
AT zhangzhenhai arobustplanarmarkerbasedvisualslam
AT zhuwei arobustplanarmarkerbasedvisualslam
AT huxuehai arobustplanarmarkerbasedvisualslam
AT denghongbin arobustplanarmarkerbasedvisualslam
AT heguang arobustplanarmarkerbasedvisualslam
AT kangxiao arobustplanarmarkerbasedvisualslam
AT wangzhoubo robustplanarmarkerbasedvisualslam
AT zhangzhenhai robustplanarmarkerbasedvisualslam
AT zhuwei robustplanarmarkerbasedvisualslam
AT huxuehai robustplanarmarkerbasedvisualslam
AT denghongbin robustplanarmarkerbasedvisualslam
AT heguang robustplanarmarkerbasedvisualslam
AT kangxiao robustplanarmarkerbasedvisualslam