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Hilti-Oxford Dataset: a millimeter-accurate benchmark for simultaneous localization and mapping

Abstract:

Simultaneous Localization and Mapping (SLAM) is being deployed in real-world applications, however many state-of-the-art solutions still struggle in many common scenarios. A key necessity in progressing SLAM research is the availability of high-quality datasets and fair and transparent benchmarking. To this end, we have created the Hilti-Oxford Dataset, to push state-of-the-art SLAM systems to their limits. The dataset has a variety of challenges ranging from sparse and regular construction s...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/LRA.2022.3226077

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-2108-5184
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0003-2675-9421
Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Robotics and Automation Letters More from this journal
Volume:
8
Issue:
1
Pages:
408-415
Publication date:
2022-12-01
Acceptance date:
2022-11-16
DOI:
EISSN:
2377-3766
Language:
English
Keywords:
Pubs id:
1314335
Local pid:
pubs:1314335
Deposit date:
2023-03-10

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