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U-VIO: Tightly Coupled UWB Visual Inertial Odometry for Robust Localization

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Robot Intelligence Technology and Applications 6 (RiTA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 429))

Abstract

The conventional visual-inertial odometry (VIO)-based localization techniques perform well in environments where stable features are guaranteed. However, their performance is not assured in poor feature quality and quantity conditions. As a solution to this, the U-VIO, a tightly coupled UWB visual-inertial odometry algorithm, is proposed in this paper. In the front-end, distance measurement between a static UWB anchor and a keyframe was considered as a residual for pose estimation. In the back-end, after finding the loop closure relationship with the current keyframe among the previous keyframes based on visual information, UWB loop constraints were added. The proposed algorithm was evaluated with data collected using a UGV (Unmanned Ground Vehicle). In the experimental analysis, the case where the UWB factor was added only to the front-end and the case where the back-end was additionally considered were compared. The proposed algorithm that closely uses UWB factors for the entire graph structure showed the most robust pose estimation performance through these evaluations.

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Acknowledgement

This work has been supported by the Unmanned Swarm CPS Research Laboratory program of Defense Acquisition Program Administration and Agency for Defense Development. (UD190029ED)

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea

    KwangYik Jung

  2. School of Electrical Engineering, KI-AI, KI-R, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea

    SungJae Shin & Hyun Myung

Authors
  1. KwangYik Jung
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  2. SungJae Shin
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  3. Hyun Myung
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Corresponding author

Correspondence to Hyun Myung .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Jinwhan Kim

  2. Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ, USA

    Brendan Englot

  3. Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Hae-Won Park

  4. Aerospace Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Han-Lim Choi

  5. Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Hyun Myung

  6. School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Junmo Kim

  7. School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Jong-Hwan Kim

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Jung, K., Shin, S., Myung, H. (2022). U-VIO: Tightly Coupled UWB Visual Inertial Odometry for Robust Localization. In: Kim, J., et al. Robot Intelligence Technology and Applications 6. RiTA 2021. Lecture Notes in Networks and Systems, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-030-97672-9_24

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