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Towards Hybrid Reasoning for Automated Industrial Fleet Management
Örebro University, School of Science and Technology. (AASS)
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-9652-7864
2015 (English)In: 24th International Joint Conference on Artificial Intelligence, Workshop on Hybrid Reasoning, AAAI Press, 2015Conference paper, Published paper (Refereed)
Abstract [en]

More and more industrial applications require fleets of autonomous ground vehicles. Today's solutions to the management of these fleets still largely rely on fixed set-ups of the system, manually specified ad-hoc rules. Our aim is to replace current practice with autonomous fleets and fleet management systems that are easily adaptable to new set-ups and environments, can accommodate human-intelligible rules, and guarantee feasible and meaningful behavior of the fleet. We propose to cast the problem of autonomous fleet management to a meta-CSP that integrates task allocation, coordination and motion planning. We discuss design choices of the approach, and how it caters to the need for hybrid reasoning in terms of symbolic, metric, temporal and spatial constraints. We also comment on a preliminary realization of the system.

Place, publisher, year, edition, pages
AAAI Press, 2015.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-47936ISBN: 978-1-57735-738-4 (print)OAI: oai:DiVA.org:oru-47936DiVA: diva2:900492
Conference
24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, 25-31 July, 2015
Available from: 2016-02-04 Created: 2016-02-04 Last updated: 2017-10-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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