LiU Electronic Press
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Author:
Kvarnström, Jonas (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology) (APD)
Doherty, Patrick (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Title:
Automated Planning for Collaborative UAV Systems
Department:
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab
Linköping University, The Institute of Technology
Publication type:
Conference paper (Refereed)
Language:
English
In:
Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Conference:
International Conference on Control, Automation, Robotics and Vision (ICARCV
Publisher: IEEE conference proceedings
Pages:
1078-1085
Year of publ.:
2010
URI:
urn:nbn:se:liu:diva-59889
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59889
ISBN:
978-1-4244-7813-2, 978-1-4244-7814-9
Subject category:
Computer Science
SVEP category:
Computer science
Abstract(en) :

Mission planning for collaborative Unmanned Aircraft Systems (UAS:s) is a complex topic which involves trade-offs between the degree of centralization or decentralization required, the degree of abstraction in which plans are generated, and the degree to which such plans are distributed among participating UAS:s. In realistic environments such as those found in naturaland man-made catastrophes where emergency services personnelare involved, a certain degree of centralization and abstractionis necessary in order for those in charge to understand andeventually sign off on potential plans. It is also quite often thecase that unconstrained distribution of actions is inconsistentwith the loosely coupled interactions and dependencies whicharise between collaborating systems. In this article, we presenta new planning algorithm for collaborative UAS:s based oncombining ideas from forward chaining planning with partialorderplanning leading to a new hybrid partial order forwardchaining(POFC) framework which meets the requirements oncentralization, abstraction and distribution we find in realisticemergency services settings.

Available from:
2010-09-29
Created:
2010-09-29
Last updated:
2013-08-29
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