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Published in: Information Systems Frontiers 1/2019

19-05-2018

Integrated Synthesis and Execution of Optimal Plans for Multi-Robot Systems in Logistics

Authors: Francesco Leofante, Erika Ábrahám, Tim Niemueller, Gerhard Lakemeyer, Armando Tacchella

Published in: Information Systems Frontiers | Issue 1/2019

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Abstract

Model-based synthesis allows to generate plans to achieve high-level tasks while satisfying certain properties of interest. However, when such plans are executed on concrete systems, several modeling assumptions may be challenged, jeopardizing their real applicability. This paper presents an integrated system for generating, executing and monitoring optimal-by-construction plans for multi-robot systems. This system unites the power of Optimization Modulo Theories with the flexibility of an on-line executive, providing optimal solutions for high-level task planning, and runtime feedback on their feasibility. After presenting how our system orchestrates static and runtime components, we demonstrate its capabilities using the RoboCup Logistics League as testbed. We do not only present our final solution but also its chronological development, and draw some general observations for the development of OMT-based approaches.

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Footnotes
2
Fawkes is a component-based software framework for robotic real-time applications. URL: www.​fawkesrobotics.​org
 
4
Running on a machine running Ubuntu Mate 16.4, Intel Core i7 CPU at 2.10GHz and 8GB of RAM
 
6
We use a machine running Debian 9, Intel Core 2 Quad CPU Q9450 at 2.66 GHz.
 
7
Makespan for non-temporal POPF with single robot is computed as follows. We read the sequence of actions contained in the plan and assign to each the same duration specified in the temporal models used by other approaches.
 
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Metadata
Title
Integrated Synthesis and Execution of Optimal Plans for Multi-Robot Systems in Logistics
Authors
Francesco Leofante
Erika Ábrahám
Tim Niemueller
Gerhard Lakemeyer
Armando Tacchella
Publication date
19-05-2018
Publisher
Springer US
Published in
Information Systems Frontiers / Issue 1/2019
Print ISSN: 1387-3326
Electronic ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-018-9858-3

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