A skill-based approach towards hybrid assembly

Frank Wallhoff, Jürgen Blume, Alexander Bannat, Wolfgang Rösel, Claus Lenz, Alois Knoll

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Efficient cooperation of humans and industrial robots is based on a common understanding of the task as well as the perception and understanding of the partner's action in the next step. In this article, a hybrid assembly station is presented, in which an industrial robot can learn new tasks from worker instructions. The learned task is performed by both the robot and the human worker together in a shared workspace. This workspace is monitored using multi-sensory perception for detecting persons as well as objects. The environmental data are processed within the collision avoidance module to provide safety for persons and equipment. The real-time capable software architecture and the orchestration of the involved modules using a knowledge-based system controller is presented. Finally, the functionality is demonstrated within an experimental cell in a real-world production scenario.

Original languageEnglish
Pages (from-to)329-339
Number of pages11
JournalAdvanced Engineering Informatics
Issue number3
StatePublished - Aug 2010


  • Adaptive control
  • Hybrid assembly
  • Instruction based learning
  • Multi-modal interaction
  • Worker surveillance


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