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Deep neural network based inertial odometry using low-cost inertial measurement units

Abstract:

Inertial measurement units (IMUs) have emerged as an essential component in many of today's indoor navigation solutions due to their low cost and ease of use. However, despite many attempts for reducing the error growth of navigation systems based on commercial-grade inertial sensors, there is still no satisfactory solution that produces navigation estimates with long-time stability in widely differing conditions. This paper proposes to break the cycle of continuous integration used in tradit...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/tmc.2019.2960780

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Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
Pembroke College
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers (IEEE) Publisher's website
Journal:
IEEE Transactions on Mobile Computing Journal website
Pages:
1-1
Publication date:
2019-12-19
DOI:
EISSN:
1558-0660
ISSN:
1536-1233

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