Publikationen

In: The 29th CIRP Conference on Life Cycle Engineering. CIRP Conference on Life Cycle Engineering (CIRP LCE-2022) April 4-6 Leuven Belgium Seiten 122-127 Procedia CIRP 105 Elsevier 2022.

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In: Computing Research Repository eprint Journal (CoRR) abs/2103.00583 Seiten 1-12 IEEE 2021.

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In: Procedia Manufacturing 55 Seiten 191-199 Elsevier 2021.

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In: 26th International Conference on Emerging Technologies and Factory Automation. IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) IEEE 9/2021.

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In: Procedia Manufacturing 55 Seiten 535-542 Elsevier 2021.

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In: Procedia CIRP CIRP Proceedings. CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME) Italy 15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 14-16 July 2019, Gulf of Naples, Italy Elsevier B.V. 2021.

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CIRP Conference on Manufactoring Systems (CIRP CMS-2021) 54th CIRP Conference on Manufacturing Systems, 2021 CIRP September 22-24 Athens Greece ELSEVIER 2021.

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International Conference on Electrical, Computer, Communications and Mechatronics Engineering 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering October 7-8 Belle Mare Mauritius IEEE 2021.

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In: Robotics and Computer-Integrated Manufacturing 68 Seiten 1-13 Elsevier BV 1/2021.

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In: IFAC-PapersOnLine 54 1 Seiten 276-281 Elsevier 2021.

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Publikationen

Aktive Filter:

Towards a Digital Lifecycle Passport for the Circular Economy

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

An OPC UA Model of the Skill Execution Interaction Protocol for the Active Asset Administration Shell

Concept for Modeling and Usage of Functionally Described Capabilities and Skills

Electrical Energy Consumption Interface in Modular Skill-Based Production Systems with the Asset Administration Shell

Using Multi-Agent Deep Reinforcement Learning For Flexible Job Shop Scheduling Problems

Simultaneous Production and AGV Scheduling using Multi-Agent Deep Reinforcement Learning

Utilizing Multi-Agent Deep Reinforcement Learning For Flexible Job Shop Scheduling Under Sustainable Viewpoints

Flatness Based Control of an Industrial Robot Joint Using Secondary Encoders

Integration of a feasibility and context check into an OPC UA skill

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