Spherical Panoramic Image-based Localization by Deep Learning
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- UMEDA Masataka
- Graduate School of Systems and Information Engineering, University of Tsukuba
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- DATE Hisashi
- Faculty of Engineering, Information and Systems, University of Tsukuba
Bibliographic Information
- Other Title
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- 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
- シンソウ ガクシュウ オ モチイタ ゼン テンキュウ パノラマ ガゾウ カラ ノ ジコ イチ スイテイ
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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
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- Transactions of the Society of Instrument and Control Engineers
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Transactions of the Society of Instrument and Control Engineers 54 (5), 483-493, 2018
The Society of Instrument and Control Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1390282763010271744
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- NII Article ID
- 130006743781
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- NII Book ID
- AN00072392
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- ISSN
- 18838189
- 04534654
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- NDL BIB ID
- 029071785
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed