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Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-4527-7586
Oxford Robotics Institute, University of Oxford, UK.
Oxford Robotics Institute, University of Oxford, UK.
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-9652-7864
2019 (English)In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019, p. 478-484Conference paper, Published paper (Refereed)
Abstract [en]

We present a novel modelling and planning approach for multi-robot systems under uncertain travel times. The approach uses generalised stochastic Petri nets (GSPNs) to model desired team behaviour, and allows to specify safety constraints and rewards. The GSPN is interpreted as a Markov decision process (MDP) for which we can generate policies that optimise the requirements. This representation is more compact than the equivalent multi-agent MDP, allowing us to scale better. Furthermore, it naturally allows for asynchronous execution of the generated policies across the robots, yielding smoother team behaviour. We also describe how the integration of the GSPN with a lower-level team controller allows for accurate expectations on team performance. We evaluate our approach on an industrial scenario, showing that it outperforms hand-crafted policies used in current practice.

Place, publisher, year, edition, pages
2019. p. 478-484
Keywords [en]
Multi-agent planning, robot planning, planning with uncertainy
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-75820OAI: oai:DiVA.org:oru-75820DiVA, id: diva2:1343600
Conference
The 28th International Joint Conference on Artificial Intelligence (IJCAI19), August 10-16, Macao, China
Available from: 2019-08-18 Created: 2019-08-18 Last updated: 2019-08-19

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CiteExportLink to record
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Citation style
  • apa
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