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Real-time order dispatching for a fleet of autonomous mobile robots using multi-agent reinforcement learningMalus, Andreja ; Kozjek, Dominik ; Vrabič, RokAutonomous mobile robots (AMRs) are increasingly being used to enable efficient material flow in dynamic production environments. Dispatching transport orders in such environments is difficult due to ... the complexity arising from the rapid changes in the environment as well as due to a tight coupling between dispatching, path planning, and route execution. For order dispatching, an approach is proposed that uses multi-agent reinforcement learning, where AMR agents learn to bid on orders based on their individual observations. The approach is investigated in a robot simulation environment. The results show a more efficient order allocation compared to commonly used dispatching rules.Source: CIRP annals. - ISSN 0007-8506 (Vol. 69, iss. 1, 2020, str. 397-400)Type of material - article, component partPublish date - 2020Language - englishCOBISS.SI-ID - 24176643
Author
Malus, Andreja |
Kozjek, Dominik |
Vrabič, Rok
Topics
logistics |
machine learning |
distributed control |
logistika |
strojno učenje |
porazdeljeno krmiljenje
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Malus, Andreja | 50105 |
Kozjek, Dominik | 38151 |
Vrabič, Rok | 30914 |
Source: Personal bibliographies
and: SICRIS
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