Decision-making under uncertainty for multi-robot systems

In this overview paper, we present the work of the Goal-Oriented Long-Lived Systems Lab on multi-robot systems. We address multi-robot systems from a decision-making under uncertainty perspective, proposing approaches that explicitly reason about the inherent uncertainty of action execution, and how...

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Bibliographic Details
Published in:Ai communications 2022-01, Vol.35 (4), p.433-441
Main Authors: Lacerda, Bruno, Gautier, Anna, Rutherford, Alex, Stephens, Alex, Street, Charlie, Hawes, Nick
Format: Article
Language:English
Subjects:
Decision making
Multiple robots
Uncertainty
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Summary:In this overview paper, we present the work of the Goal-Oriented Long-Lived Systems Lab on multi-robot systems. We address multi-robot systems from a decision-making under uncertainty perspective, proposing approaches that explicitly reason about the inherent uncertainty of action execution, and how such stochasticity affects multi-robot coordination. To develop effective decision-making approaches, we take a special focus on (i) temporal uncertainty, in particular of action execution; (ii) the ability to provide rich guarantees of performance, both at a local (robot) level and at a global (team) level; and (iii) scaling up to systems with real-world impact. We summarise several pieces of work and highlight how they address the challenges above, and also hint at future research directions.
ISSN:0921-7126
1875-8452
DOI:10.3233/AIC-220118