盲眼SLAM:一种高效的基于特征的单目SLAM系统

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI:10.1109/YAC57282.2022.10023629

Feng Yang, Baibing Jie, Hongxuan Song, Haotian Li

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引用次数: 0

摘要

特征匹配质量对基于特征的同步定位与映射(SLAM)系统的鲁棒性和定位精度起着至关重要的作用，其中描述符对跟踪和再定位具有重要意义。本文提出了一种高效的基于特征的单目SLAM系统beblind -SLAM，该系统使用beblind描述符对ORB-SLAM管道中的特征进行匹配。在本系统中，分别采用直方图均衡化对输入图像进行预处理，采用离线训练Bag-of-Words进行beblind预处理，实现输入图像的再定位和闭环。此外，我们在公共数据集EuRoC中验证了我们的算法在鲁棒性和准确性方面比流行的算法有突出的表现

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BEBLID-SLAM: An Efficient Feature-Based Monocular SLAM System

The feature matching quality plays an important role in the robustness and location accuracy of feature-based Simultaneous Localization and Mapping (SLAM) system, in which descriptor is significant of tracking and re-localization. In this paper, we propose an efficient feature-based Monocular SLAM system, BEBLID-SLAM, which use BEBLID descriptor for feature matching in ORB-SLAM pipeline. In the proposed system, adopting histogram equalization to preprocess input images and offline training Bag-of-Words for BEBLID is respectively adopted to preprocess input images and realize re-localization and loop closure. Moreover, we valided that our algorithm has outstanding performance in robustness and accuracy than the popular algorithms in the public dataset EuRoC

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2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)

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