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Position-Pose Measurement Algorithm Based on Geometrical Characteristics

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Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13458))

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Abstract

Based on the geometrical characteristics, this paper proposes a position-pose measurement algorithm with the non-feature point data of the cooperative target. This method only needs to project six parallel laser beams to the target and obtain the range-finding result without knowing the coordinates of measurement points in target system, then the position-pose of target and the object fixed to it can be figured out. This algorithm is verified by establishing the model of the cooperative target and the position-pose measurement system. The experimental results show that the average absolute error of the pose rotation measured by the algorithm is stable within 0.5°, and the movement is within 1 mm.

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Acknowledgement

This research was supported by the National Natural Science Foundation of China (Grant No. 51975344).

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Authors and Affiliations

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China

    Ben Shi & Xu Zhang

  2. Huazhong University of Science and Technology Wuxi Research Institute, Wuxi, China

    Xu Zhang

Authors
  1. Ben Shi
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  2. Xu Zhang
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Corresponding author

Correspondence to Xu Zhang .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Honghai Liu

  2. Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

  3. Shenyang Institute of Automation, Shenyang, Liaoning, China

    Lianqing Liu

  4. Harbin Institute of Technology, Harbin, China

    Li Jiang

  5. Shanghai Jiao Tong University, Shanghai, China

    Guoying Gu

  6. Shenzhen Institute of Advanced Technology, Shenzhen, China

    Xinyu Wu

  7. Harbin Institute of Technology, Shenzhen, China

    Weihong Ren

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Shi, B., Zhang, X. (2022). Position-Pose Measurement Algorithm Based on Geometrical Characteristics. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13458. Springer, Cham. https://doi.org/10.1007/978-3-031-13841-6_69

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  • DOI: https://doi.org/10.1007/978-3-031-13841-6_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13840-9

  • Online ISBN: 978-3-031-13841-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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