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An AGV Positioning Algorithm for Reducing the Number of Reflectors

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13455))

Abstract

Aiming at the problem of low global positioning precision and a large number of reflectors in the global feature map, an AGV positioning algorithm for reducing the number of reflectors is proposed. First, the global feature map is constructed by the reflectors. Next, the reflection points are obtained by lidar scanning, in which abnormal reflection points are removed through preprocessing. The local coordinates of the reflector are clustered and fitted by combining the reflection intensity of the reflector point. Then, the global coordinates of the reflectors are obtained by matching the local coordinates of the reflector with the global feature map. Finally, the initial position of the AGV is obtained through the static pose calculation algorithm, and the dynamic position of the AGV is solved by the two-point positioning algorithm. The experimental results show that, compared with the traditional algorithm, the positioning algorithm based on reflectors in this paper decreases the global position precision by 42.0% and 16.1% in the X-axis and Y-axis, respectively, and the number of reflectors used for the positioning algorithm is reduced from three or more to two.

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Acknowledgement

This work was supported in part by the National Natural Science Foundation of China under Grant NSFC U1813212, in part by the Science and Tech-nology Planning Project of Guangdong Province, China under Grant 2020B121201012.

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Correspondence to Guang-Zhong Cao .

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Luo, Y., Cao, GZ., Wu, C., Hu, ZY. (2022). An AGV Positioning Algorithm for Reducing the Number of Reflectors. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13455. Springer, Cham. https://doi.org/10.1007/978-3-031-13844-7_27

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  • DOI: https://doi.org/10.1007/978-3-031-13844-7_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13843-0

  • Online ISBN: 978-3-031-13844-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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