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Online Task Assignment and Coordination in Multi-Robot Fleets
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-4784-5089
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-1627-0921
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9652-7864
2021 (English)In: IEEE Robotics and Automation Letters, E-ISSN 2377-3766, Vol. 6, no 3, p. 4584-4591Article in journal (Refereed) Published
Abstract [en]

We propose a loosely-coupled framework for integrated task assignment, motion planning, coordination and contro of heterogeneous fleets of robots subject to non-cooperative tasks. The approach accounts for the important real-world requiremen that tasks can be posted asynchronously. We exploit systematic search for optimal task assignment, where interference is considered as a cost and estimated with knowledge of the kinodynamic models and current state of the robots. Safety is guaranteed by an online coordination algorithm, where the absence of collisions is treated as a hard constraint. The relation between the weight of interference cost in task assignment and computational overhead is analyzed empirically, and the approach is compared against alternative realizations using local search algorithms for task assignment.

Place, publisher, year, edition, pages
IEEE Press, 2021. Vol. 6, no 3, p. 4584-4591
Keywords [en]
Planning, scheduling and coordination, task and motion planning, multi-robot systems
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-90583DOI: 10.1109/LRA.2021.3068918ISI: 000640765600021Scopus ID: 2-s2.0-85103259479OAI: oai:DiVA.org:oru-90583DiVA, id: diva2:1538478
Funder
EU, Horizon 2020, 858101Knowledge FoundationVinnovaAvailable from: 2021-03-19 Created: 2021-03-19 Last updated: 2024-01-17Bibliographically approved

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Forte, PaoloMannucci, AnnaAndreasson, HenrikPecora, Federico

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  • apa
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