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Multi-Objective Search for Optimal Multi-Robot Planning with Finite LTL Specifications and Resource Constraints
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. Bosch Center for Artificial Intelligence, Germany.
Bosch Center for Artificial Intelligence, Germany.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0001-7309-8086
2017 (English)In: 2017 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2017, 768-774 p., 7989094Conference paper, Published paper (Refereed)
Abstract [en]

We present an efficient approach to plan action sequences for a team of robots from a single finite LTL mission specification. The resulting execution strategy is proven to solve the given mission with minimal team costs, e.g., with shortest execution time. For planning, an established graphbased search method based on the multi-objective shortest path problem is adapted to multi-robot planning and extended to support resource constraints. We further improve planning efficiency significantly for missions which consist of independent parts by using previous results regarding LTL decomposition. The efficiency and practicality of the ROS implementation of our approach is demonstrated in example scenarios.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. 768-774 p., 7989094
Series
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keyword [en]
ltl, robot, robotics, multi-agent, behavior synthesis, formal methods, decomposition, high-level planning, multi-objective search, resource constraints
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-204949DOI: 10.1109/ICRA.2017.7989094Scopus ID: 2-s2.0-85027993404ISBN: 9781509046331 (print)OAI: oai:DiVA.org:kth-204949DiVA: diva2:1087182
Conference
IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29 - June 3, 2017
Funder
EU, Horizon 2020, 731869
Note

QC 20170705

Available from: 2017-04-06 Created: 2017-04-06 Last updated: 2017-09-04Bibliographically approved

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Schillinger, PhilippDimarogonas, Dimos V.
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