KI - Künstliche Intelligenz

, Volume 29, Issue 4, pp 407–411 | Cite as

Open-EASE: A Cloud-Based Knowledge Service for Autonomous Learning

  • Moritz Tenorth
  • Jan Winkler
  • Daniel Beßler
  • Michael Beetz
Research Project


We present Open-EASE, a cloud-based knowledge base of robot experience data that can serve as episodic memory, providing a robot with comprehensive information for autonomously learning manipulation tasks. Open-EASE combines both robot and human activity data in a common, semantically annotated knowledge base, including robot poses, object information, environment models, the robot’s intentions and beliefs, as well as information about the actions that have been performed. A powerful query language and inference tools support reasoning about the data and retrieving information based on semantic queries. In this paper, we focus on applications of Open-EASE in the context of autonomous learning.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Moritz Tenorth
    • 1
  • Jan Winkler
    • 1
  • Daniel Beßler
    • 1
  • Michael Beetz
    • 1
  1. 1.Institute for Artificial IntelligenceUniversität BremenBremenGermany

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