深層学習を用いた全天球パノラマ画像からの自己位置推定  [in Japanese] Spherical Panoramic Image-based Localization by Deep Learning  [in Japanese]

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Author(s)

    • 梅田 将孝 UMEDA Masataka
    • 筑波大学大学院システム情報工学研究科 Graduate School of Systems and Information Engineering, University of Tsukuba
    • 伊達 央 DATE Hisashi
    • 筑波大学システム情報系 Faculty of Engineering, Information and Systems, University of Tsukuba

Abstract

<p>The goal of our research is to construct intelligence for autonomous robots which navigate through the real world using images from attached cameras. Localization is one of the key elements for autonomous navigation. In this paper, we propose a grid-based localization from a single image using deep learning. By using a grid map, uncertainty of localization can be defined in a natural way, which is useful for fusion with other sensors The network takes spherical panoramic images with position and orientation of the robot as training data. Position and orientation are expressed by multi-dimensional grid. The network behaves as a classifier, where each grid corresponds to indivisual class and its probability represents that of position and orientation. The experimental results support the effectiveness of the proposed method.</p>

Journal

  • Transactions of the Society of Instrument and Control Engineers

    Transactions of the Society of Instrument and Control Engineers 54(5), 483-493, 2018

    The Society of Instrument and Control Engineers

Codes

  • NII Article ID (NAID)
    130006743781
  • NII NACSIS-CAT ID (NCID)
    AN00072392
  • Text Lang
    JPN
  • ISSN
    0453-4654
  • NDL Article ID
    029071785
  • NDL Call No.
    Z14-482
  • Data Source
    NDL  J-STAGE 
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