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Advisor(s)
Abstract(s)
Automated guided vehicles (AGV) represent a key element in
industries’ intralogistics and the use of AGV fleets bring multiple advantages.
Nevertheless, coordinating a fleet of AGV is already a complex
task but when exposed to delays in the trajectory and communication
faults it can represent a threat, compromising the safety, productivity
and efficiency of these systems. Concerning this matter, trajectory planning
algorithms allied with supervisory systems have been studied and
developed. This article aims to, based on work developed previously,
implement and test a Multi AGV Supervisory System on real robots and
analyse how the system responds to the dynamic of a real environment,
analysing its intervention, what influences it and how the execution time
is affected.
Description
Keywords
Multi AGV coordination Time enhanced A* Real implementation
Citation
Cruz, Ana; Matos, Diogo; Lima, José; Costa, Paulo; Costa, Pedro (2021). Multi AGV industrial supervisory system. In Pereira, Ana I.; Fernandes, Florbela P.; Coelho, João Paulo; Teixeira, João Paulo; Pacheco, Maria F.; Alves, Paulo; Lopes, Rui Pedro (Eds.) Optimization, learning algorithms and applications: first International Conference, OL2A 2021. Cham: Springer Nature. p. 203-218. ISBN 978-3-030-91884-2
Publisher
Springer Nature