ROOKIE – Improving Flexibility in Assembly Using an Ontology and AI-Based Methodology with Integrated Expert Knowledge

Key Info

Basic Information

01.02.2023 to 31.01.2025
Organizational Unit:
Chair of Machine Tools, Automation and Control
Federation of Industrial Research Associations "Otto-von-Guericke" e.V. (AiF)

Research partner

    • 3M Deutschland GmbH
    • 3win Maschinenbau GmbH
    • aiXbrain GmbH
    • Basler AG
    • CAMaix GmbH
    • EXAPT Systemtechnik GmbH
    • Forschungsvereinigung Programmiersprachen für Fertigungseinrichtungen e.V.
    • Heinen Automation GmbH & Co. KG
    • IDS Imaging Development Systems GmbH
    • Maschinentechnik Müller GmbH
    • Module Works GmbH
    • Neura Robotics GmbH
    • Niederrhein Automation GmbH
    • Schiffer Metall- & Vakuumtechnik GmbH
    • TQ-Group GmbH
    • Xenon Automatisierungstechnik GmbH
    • YOUSE GmbH
    • Center Smart Industrial Agriculture
    • Chamber of Crafts Koblenz
    • KSB SE& Co. KgaA



+49 241 80 20224



Due to a wide variety of variants, short product life cycles and small batch sizes, small and medium-sized businesses often resort to manual processes in assembly. Compared to an automation solution, this leads to high labor costs and varying quality of the products. A technology combination that has the potential to counteract this problem is AI-based robotics. Using AI, robot-based applications can be implemented flexibly, autonomously and robustly. This means that automation can be justified even with smaller quantities and the risk of bad investments can be reduced. Hereby, one challenge is to get the required data quality and quantity for training the AI models, which is often difficult to achieve, especially with small quantities.

As part of the proposed research project „ROOKIE“, a comprehensive methodology with an ontology-based modeling approach and synthetic data generation is developed, which enables the use of AI-based robot operations in industrial assembly. This should increase the flexibility, autonomy and robustness of the planning, commissioning and execution of robot-based assembly operations, and result in accessibility of autonomous assembly processes for small and medium-sized businesses.

Possible solutions are the enrichment of smaller data sets with known engineering information in combination with the integration of expert knowledge. AI algorithms are used to enable flexible and automated execution of assembly operations.