Task Variant Allocation in Distributed Robotics

Cano, J. , White, D. R., Bordallo, A., McCreesh, C., Prosser, P., Singer, J. and Nagarajan, V. (2016) Task Variant Allocation in Distributed Robotics. In: Robotics Science and Systems 2016, Ann Arbor, MI, USA, 18-22 June 2016, ISBN 9780992374723 (doi:10.15607/RSS.2016.XII.045)

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Abstract

This paper tackles the problem of allocating tasks to a distributed heterogeneous robotic system, where tasks---named *task variants* in the paper---can vary in terms of trade-off between resource requirements and quality of service provided. Three different methods (constraint programming, greedy, and metaheuristic) are proposed to solve such a problem and are evaluated both in simulation and in a real scenario, showing the goodness of the constraint programming method.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Singer, Dr Jeremy and Prosser, Dr Patrick and Cano Reyes, Dr Jose and Mccreesh, Dr Ciaran and White, Dr David
Authors: Cano, J., White, D. R., Bordallo, A., McCreesh, C., Prosser, P., Singer, J., and Nagarajan, V.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Robotics Science and Systems 2016
ISBN:9780992374723
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in Robotics Science and Systems 2016
Publisher Policy:Reproduced with permission of the Editor
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
614231AnyScale ApplicationsJeremy SingerEngineering & Physical Sciences Research Council (EPSRC)EP/L000725/1COM - COMPUTING SCIENCE