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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. Bosch Center for Artificial Intelligence.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0001-7309-8086
Bosch Center for Artificial Intelligence.
2017 (English)Conference 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
2017.
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-204949OAI: 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
Available from: 2017-04-06 Created: 2017-04-06 Last updated: 2017-04-06

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Citation style
  • apa
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  • de-DE
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