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Point and Line Feature-Based VIO for Mobile Devices

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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))

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Abstract

Localization is an important task in various fields. Especially, a robust and accurate localization system is required for a mobile device to be used in AR (augmented reality) or MR (mixed reality) applications. In this paper, we present an accurate visual-inertial odometry algorithm based on both point and line features. This algorithm utilizes a sliding window non-linear optimization-based method to reduce the computational cost. We implemented our proposed algorithm on a smartphone. Also, we show that our proposed algorithm works well in indoor and outdoor environments in real-time.

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Acknowledgement

This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No. 2021-0-00230, development of real\(\cdot \)virtual environmental analysis based adaptive interaction technology) and the Defense Challengeable Future Technology Program of Agency for Defense Development, Republic of Korea. The students are supported by Korea Ministry of Land, Infrastructure and Transport (MOLIT) as “Innovative Talent Education Program for Smart City” and BK21 FOUR.

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Authors and Affiliations

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

    Yeeun Kim, Hyunjun Lim & Hyun Myung

Authors
  1. Yeeun Kim
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  2. Hyunjun Lim
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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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Kim, Y., Lim, H., Myung, H. (2022). Point and Line Feature-Based VIO for Mobile Devices. 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_25

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