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Simultaneous task allocation and planning under uncertainty

Abstract:

We propose novel techniques for task allocation and planning in multi-robot systems operating in uncertain environments. Task allocation is performed simultaneously with planning, which provides more detailed information about individual robot behaviour, but also exploits independence between tasks to do so efficiently. We use Markov decision processes to model robot behaviour and linear temporal logic to specify tasks and safety constraints. Building upon techniques and tools from formal ver...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/IROS.2018.8594404

Authors


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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
Department:
Engineering Science
Oxford college:
Pembroke College
Role:
Author
ORCID:
0000-0002-7556-6098
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Funding agency for:
Lacerda, B
Grant:
EP/R026084/1
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Funding agency for:
Hawes, N
Grant:
EP/R026084/1
Defense Advanced Research Projects Agency More from this funder
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018) Journal website
Host title:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)
Publication date:
2019-01-22
Acceptance date:
2018-06-29
DOI:
Source identifiers:
866478
Keywords:
Pubs id:
pubs:866478
UUID:
uuid:0b5fc425-f598-48cc-92c6-525df027525a
Local pid:
pubs:866478
Deposit date:
2018-11-16

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