Planning, Training and Learning in Supervision of Flexible Assembly Systems

Luís Manuel Camarinha-Matos, Luis Seabra Lopes

Research output: Chapter in Book/Report/Conference proceedingForeword/postscriptpeer-review


In the context of balanced automation systems, a generic architecture for evolutive supervision of robotized assembly tasks is presented. This architecture provides, at various abstraction levels, functions for dispatching actions, execution monitoring, and diagnosing and recovering from failures. A planning strategy and domain knowledge for nominal plan execution and error recovery is described. Through the use of machine learning techniques, the supervision architecture will be given capabilities to improve its performance over time. The participation of humans in the training and supervision activities is considered essential. The combination of human interactivity with automatic aspects (planning, learning,..) is discussed.
Original languageEnglish
Title of host publicationBalanced Automation Systems
Number of pages12
ISBN (Print)0-412-72200-3
Publication statusPublished - Jan 1995
EventBASYS'95 – IEEE/IFIP Int. Conf. On Balanced Automation Systems - Victoria, Brazil
Duration: 23 Jul 199526 Jul 1995


ConferenceBASYS'95 – IEEE/IFIP Int. Conf. On Balanced Automation Systems
Abbreviated titleBASYS'95


  • Robotized assembly
  • action sequence planning
  • monitoring
  • failure diagnosis
  • machine learning


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