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Visual Simultaneous Localization and Mapping (SLAM) Based on Blurred Image Detection

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Abstract

For a moving robot based on visual Simultaneous Localization and Mapping (SLAM), blurred images will degrade the accuracy of localization. Therefore, how to handle blurred images is a main problem in visual SLAM. In order to decrease the influence of blurred images on localization accuracy, this paper proposes an improved visual SLAM, which is based on Haar wavelet transform and has the ability of eliminating blurred images. Besides, a correlation-weighted pose optimization is also developed in this paper. This weighted optimization integrates the correlation between matching features as weighting coefficients into the reprojection errors. In this weighted method, pose optimization algorithm can reduce the influence of the matching features with low correlation, which are more likely to be mismatched. As a result, the accuracy of the estimated pose will be improved. The improved system optimized by our method is evaluated on the TUM RGB-D dataset and real environment. It is also compared with other optimization systems, which were based on blurred image elimination and uncertainty-weighted optimization respectively. The experimental results demonstrate that the system optimized by our method could achieve the highest accuracy and robustness in pose estimation.

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Funding

This work was supported in part by the National Natural Science Foundation of China (No. 61672084 and No. 61973333) and the Fundamental Research Funds for the Central Universities (No. XK1802–4).

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Authors and Affiliations

  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China

    Huaiyuan Yu & Haijiang Zhu

  2. School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, CO, China

    Fengrong Huang

Authors
  1. Huaiyuan Yu
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  2. Haijiang Zhu
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  3. Fengrong Huang
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Contributions

Conceptualization, Huaiyuan Yu, Haijiang Zhu, and Fengrong Huang; Data curation, Huaiyuan Yu; Formal analysis, Huaiyuan Yu; Funding acquisition, Haijiang Zhu and Fengrong Huang; Methodology, Huaiyuan Yu; Software, Huaiyuan Yu; Supervision, Haijiang Zhu and Fengrong Huang; Validation, Huaiyuan Yu; Writing – original draft, Huaiyuan Yu; Writing – review and editing, Huaiyuan Yu and Haijiang Zhu.

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Correspondence to Haijiang Zhu or Fengrong Huang.

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Yu, H., Zhu, H. & Huang, F. Visual Simultaneous Localization and Mapping (SLAM) Based on Blurred Image Detection. J Intell Robot Syst 103, 12 (2021). https://doi.org/10.1007/s10846-021-01456-5

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  • DOI: https://doi.org/10.1007/s10846-021-01456-5

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