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Next best view planning for object recognition in mobile robotics

Abstract:

Recognising objects in everyday human environments is a challenging task for autonomous mobile robots. However, actively planning the views from which an object might be perceived can significantly improve the overall task performance. In this paper we have designed, developed, and evaluated an approach for next best view planning. Our view planning approach is based on online aspect graphs and selects the next best view after having identified an initial object candidate. The approach has tw...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Pembroke College
Role:
Author
ORCID:
0000-0002-7556-6098
Publisher:
CEUR Workshop Proceedings Publisher's website
Journal:
CEUR Workshop Proceedings Journal website
Volume:
1782
Pages:
1-9
Host title:
Proceedings of the 34th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG 2016), Huddersfield, United Kingdom, December 15-16, 2016
Publication date:
2017-01-16
Acceptance date:
2016-11-04
ISSN:
1613-0073
Source identifiers:
820010
Pubs id:
pubs:820010
UUID:
uuid:2e0178b3-f9fe-4ed6-bb1a-1b88d497329f
Local pid:
pubs:820010
Deposit date:
2018-01-24

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