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Decomposition of Finite LTL Specifications for Efficient Multi-Agent Planning
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Robert Bosch GmbH.
Robert Bosch GmbH.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-7309-8086
2016 (English)In: / [ed] Roderich Gross, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Generating verifiably correct execution strategies from Linear Temporal Logic (LTL) mission specifications avoids the need for manually designed robot behaviors. However, when incorporating a team of robot agents, the additional model complexity becomes a critical issue. Given a single finite LTL mission and a team of robots, we propose an automata-based approach to automatically identify possible decompositions of the LTL specification into sets of independently executable task specifications. Our approach leads directly to the construction of a team model with significantly lower complexity than other representations constructed with conventional methods. Thus, it enables efficient search for an optimal decomposition and allocation of tasks to the robot agents.

Place, publisher, year, edition, pages
2016.
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438
Keyword [en]
ltl, robot, robotics, multi-agent, behavior synthesis, formal methods, decomposition
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-199915OAI: oai:DiVA.org:kth-199915DiVA, id: diva2:1066392
Conference
13th International Symposium on Distributed Autonomous Robotic Systems, London, November 6-9, 2016.
Funder
Swedish Research Council
Note

QC 20170201

Available from: 2017-01-18 Created: 2017-01-18 Last updated: 2017-02-01Bibliographically approved

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