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An efficient loop closure detection method based on spatially constrained feature matching

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Abstract

Loop detection technology is an important part of the simultaneous localization and mapping system for eliminating the pose drift of robots during long-term movement. In order to solve the three main challenges of appearance-based methods, namely viewpoint changes, repeated textures, and large amounts of calculation, this paper proposes an unsupervised loop detection method that takes into account both the texture pattern and position information of feature points and avoids any pre-training steps. Since the relative rotation and translation of the robot between two frames forming loop closure are both very small, the proposed method constrains the matching range with an overlapped block strategy to not only improve the matching precision, but also reduce the cost of matching. Furthermore, the method introduces Gaussian functions to weight and fuse the matching score of each block. The proposed method is evaluated in detail on two different public datasets with various scenarios, and the results show that the proposed method performs better and more efficiently than existing state-of-the-art methods.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Funding

This work is supported by the National Key Research and Development Program of China (2018YFB1307402).

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Authors and Affiliations

  1. Perception, Machine Control and Intelligent Robot Innovation Lab. (PMCIRI.), College of Electrical Engineering, Sichuan University, Chengdu, 610065, China

    Hong Zhang, Tao Zhao, Yuzhong Zhong, Yanjie Yin, Haobin Yuan & Songyi Dian

Authors
  1. Hong Zhang
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  2. Tao Zhao
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  3. Yuzhong Zhong
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  4. Yanjie Yin
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  5. Haobin Yuan
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  6. Songyi Dian
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Contributions

YZ contributed to the conception of the study and manuscript preparation, and HZ contributed significantly to the analysis and provided most of the experimental data, he and TZ performed the data analyses and wrote the manuscript, YY and HY provided some comparative experimental results, SD helped revise the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yuzhong Zhong.

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This work is supported by the National Key Research and Development Program of China (2018YFB1307402)

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Zhang, H., Zhao, T., Zhong, Y. et al. An efficient loop closure detection method based on spatially constrained feature matching. Intel Serv Robotics 15, 363–379 (2022). https://doi.org/10.1007/s11370-022-00423-9

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  • DOI: https://doi.org/10.1007/s11370-022-00423-9

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