KR2021Proceedings of the 18th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning

Online event. November 3-12, 2021.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-99-7

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Published by

Copyright © 2021 International Joint Conferences on Artificial Intelligence Organization

Flexible Robotic Assembly Based on Ontological Representation of Tasks, Skills, and Resources

  1. Philipp Matthias Schäfer(Institute of Data Science, German Aerospace Center (DLR))
  2. Franz Steinmetz(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  3. Stefan Schneyer(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  4. Timo Bachmann(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  5. Thomas Eiband(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  6. Florian Samuel Lay(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  7. Abhishek Padalkar(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  8. Christoph Sürig(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  9. Freek Stulp(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))
  10. Korbinian Nottensteiner(Institute of Robotics and Mechatronics, German Aerospace Center (DLR))

Keywords

  1. Integrating reasoning about actions and control
  2. Multi-robot planning and coordination

Abstract

Technology has sufficiently matured to enable, in principle, flexible and autonomous robotic assembly systems. However, in practice, it requires making all the relevant (implicit) knowledge that system engineers and workers have – about products to be assembled, tasks to be performed, as well as robots and their skills – available to the system explicitly. Only then can the planning and execution components of a robotic assembly pipeline communicate with each other in the same language and solve tasks autonomously without human intervention.

This is why we have developed the Factory of the Future (FoF) ontology. At its core, this ontology models the tasks that are necessary to assemble a product and the robotic skills that can be employed to complete said tasks. The FoF ontology is based on existing standards. We started with theoretical considerations and iteratively adapted it based on practical experience gained from incorporating more and more components required for automated planning and assembly. Furthermore, we propose tools to extend the ontology for specific scenarios with knowledge about parts, robots, tools, and skills from various sources. The resulting scenario ontology serves us as world model for the robotic systems and other components of the assembly process. A central runtime interface to this world model provides fast and easy access to the knowledge during execution. In this work, we also show the integration of a graphical user front-end, an assembly planner, a workspace reconfigurator, and more components of the assembly pipeline that all communicate with the help of the FoF ontology.

Overall, our integration of the FoF ontology with the other components of a robotic assembly pipeline shows that using an ontology is a practical method to establish a common language and understanding between the involved components.