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Learning to see the wood for the trees: Deep laser localization in urban and natural environments on a CPU

Abstract:

Localization in challenging, natural environments, such as forests or woodlands, is an important capability for many applications from guiding a robot navigating along a forest trail to monitoring vegetation growth with handheld sensors. In this letter, we explore laser-based localization in both urban and natural environments, which is suitable for online applications. We propose a deep learning approach capable of learning meaningful descriptors directly from three-dimensional point clouds ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/LRA.2019.2895264

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0003-2940-0879
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Host title:
IEEE Robotics and Automation Letters
Journal:
IEEE Robotics and Automation Letters
Volume:
4
Issue:
2
Pages:
1327-1334
Publication date:
2019-01-25
Acceptance date:
2019-01-09
DOI:
ISSN:
2377-3766
Keywords:
Pubs id:
pubs:1081439
UUID:
uuid:e181235e-f4e4-408d-8235-6899d922bf59
Local pid:
pubs:1081439
Source identifiers:
1081439
Deposit date:
2020-01-09

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