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A Loosely-Coupled Approach for Multi-Robot Coordination, Motion Planning and Control, ICAPS
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9652-7864
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-4527-7586
Technical University of Varna, Varna, Bulgaria.
2018 (English)In: Proceedings of the International Conference on Automated Planning and Scheduling / [ed] Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan, Delft, The Netherlands: AAAI Press, 2018, Vol. 2018-June, p. 485-493, article id 139850Conference paper, Published paper (Refereed)
Abstract [en]

Deploying fleets of autonomous robots in real-world applications requires addressing three problems: motion planning, coordination, and control. Application-specific features of the environment and robots often narrow down the possible motion planning and control methods that can be used. This paper proposes a lightweight coordination method that implements a high-level controller for a fleet of potentially heterogeneous robots. Very few assumptions are made on robot controllers, which are required only to be able to accept set point updates and to report their current state. The approach can be used with any motion planning method for computing kinematically-feasible paths. Coordination uses heuristics to update priorities while robots are in motion, and a simple model of robot dynamics to guarantee dynamic feasibility. The approach avoids a priori discretization of the environment or of robot paths, allowing robots to “follow each other” through critical sections. We validate the method formally and experimentally with different motion planners and robot controllers, in simulation and with real robots.

Place, publisher, year, edition, pages
Delft, The Netherlands: AAAI Press, 2018. Vol. 2018-June, p. 485-493, article id 139850
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-64721ISI: 000492986200059Scopus ID: 2-s2.0-85054990876OAI: oai:DiVA.org:oru-64721DiVA, id: diva2:1178913
Conference
International Conference on Automated Planning and Scheduling (ICAPS 2018), Delft, The Netherland, June 24-29, 2018
Projects
Semantic RobotsILIAD
Funder
Knowledge Foundation, 20140033EU, Horizon 2020, 732737VinnovaAvailable from: 2018-01-31 Created: 2018-01-31 Last updated: 2019-11-12Bibliographically approved

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Pecora, FedericoAndreasson, HenrikMansouri, Masoumeh

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • Other locale
More languages
Output format
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  • asciidoc
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