A Robust Planar Marker-Based Visual SLAM

Zhoubo Wang, Zhenhai Zhang*, Wei Zhu*, Xuehai Hu, Hongbin Deng, Guang He, Xiao Kang

*此作品的通讯作者

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摘要

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.

源语言英语
文章编号917
期刊Sensors
23
2
DOI
出版状态已出版 - 1月 2023

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引用此

Wang, Z., Zhang, Z., Zhu, W., Hu, X., Deng, H., He, G., & Kang, X. (2023). A Robust Planar Marker-Based Visual SLAM. Sensors, 23(2), 文章 917. https://doi.org/10.3390/s23020917