Title:
Robot task assignment in dynamic factory environments
Authors:
- Maximilian Dilefeld
- Thorsten Claus
- Frank Herrmann
- Enrico Teich
Published in:
(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024
DOI:
https://doi.org/10.7148/2024-0338
Citation format:
Maximilian dilefeld, Thorsten claus, Frank herrmann, Enrico teich (2024). Robot task assignment in dynamic factory environments, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0338
Abstract:
Automated Guided
Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) are being applied more and
more frequently in a wide range of use cases. Following the general trend of
decentralisation of control structure in the Industry 4.0 paradigm, this paper
analyses the application of auction algorithms to solve the robot task
assignment problem. We focus on the use of mobile robots in production
environments with a high level of uncertainty which places hight demand on the
flexibility of the online scheduling architecture. A sequential single-item
(SSI) auction algorithm is validated for a real-world use case where multiple
mobile robots supply car bodies to manual rework stations in a paint shop
application using simulation. The optimization objective of such an algorithm
is discussed in regards to the examined use case.
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