KIT | KIT-Bibliothek | Impressum | Datenschutz

Multi-level optimization approach for multi-robot manufacturing systems

Ye, Xin 1; Shen, Wei 2; Mamaev, Ilshat 3; Bertram, Thomas; Bryg, Maximilian; Schwartz, Manuel ORCID iD icon 1; Hohmann, Soeren 2; Asfour, Tamim 3; Hein, Bjoern 2; Kipfmueller, Martin; Kotschenreuther, Jan
1 Institut für Regelungs- und Steuerungssysteme (IRS), Karlsruher Institut für Technologie (KIT)
2 Karlsruher Institut für Technologie (KIT)
3 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)


This paper presents a multi-level optimization approach for multi-robot system in the context of Software Defined Man-
ufacturing (SDM). While industrial robots offer larger workspace, versatility, and lower cost, they generally lack in
rigidity and thus accuracy in comparison to machine tools. We propose a solution to compensating these drawbacks
using a multi-level optimization which includes an intelligent task and action planning for multiple robots, a trajectory
generation considering robot dynamics, coupling of robots, and stiffness constraints, as well as a modular simulative
validation. Finally, we present an experimental setup with two coupled robots in a bending task. The results show this
approach allows robots to apply significantly higher forces compared to single robot setup, and dual robot benchmark
without stiffness optimization.

Zitationen: 3
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Institut für Regelungs- und Steuerungssysteme (IRS)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISBN: 978-3-8007-5891-3
KITopen-ID: 1000150792
Erschienen in 54th International Symposium on Robotics : (ISR Europe 2022) : 20-21 June 2022, Munich, Germany
Veranstaltung 54th International Symposium on Robotics (ISR Europe 2022), München, Deutschland, 20.06.2022 – 21.06.2022
Verlag VDE Verlag
Seiten 1-8
Nachgewiesen in Scopus
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page