EASE is an interdisciplinary research center at the University of Bremen that investigates everyday activity science & engineering. Everyday Activity Science and Engineering (EASE) is the study of the design, realization, and analysis of information processing models that enable robotic agents (and humans) to master complex human-scale manipulation tasks that are mundane and routine. EASE not only investigates action selection and control but also the methods needed to acquire the knowledge, skills, and competence required for flexible, reliable, and efficient mastery of these activities.


The key components are:


  • the fundamental research thread (Research) which organizes and executes the EASE research agenda
  • openEASE, which collects the community-based initiatives of EASE, including the openEASE knowledge service, the opensource software packages KNOWROB, ROBOSHERLOCK, ROBCOG, PRAC, CRAM, and GISKARD, open teaching and training efforts, as well as cooperative opportunities.
  • EASEacademy, which provides the EASE teaching and training facilities including the EASE doctoral training school, courses for students at the University of Bremen, offering for Highschool students, as well as internet teaching material
  • EASEinnovation, includes the technology transfer efforts of EASE, such as applied research and technology transfer projects, innovation activities
  • EASEoutreach provides information material for the general public and media

Seminars and Events

  1. EASE at the Automatica 2018

    June 19 - June 22
  2. EASE fall school

    September 17 - September 21
  3. EASE at IROS 2018

    October 1 - October 5


Mihai Pomarlan, John Bateman (2018):
Robot program construction via grounded natural language semantics & simulation
In AAMAS Robotics Track, 2018

A. K. Bozcuoğlu, G. Kazhoyan, Y. Furuta, S. Stelter, M. Beetz, K. Okada, M. Inaba (2018):
The Exchange of Knowledge Using Cloud Robotics
In IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1072-1079, 2018

Simon Stelter, Georg Bartels, Michael Beetz (2018):
Multidimensional Time Series Shapelets Reliably Detect and Classify Contact Events in Force Measurements of Wiping Actions
In Robotics and Automation Letters, IEEE, 2018

S. G. Brunner, P. Lehner, M. J. Schuster, S. Riedel, R. Belder, D. Leidner, A. Wedler, M. Beetz, F. Stulp (2018):
Design, Execution, and Postmortem Analysis of Prolonged Autonomous Robot Operations
In IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1056-1063, 2018

Daniel Nyga, Michael Beetz (2018):
Cloud-based Probabilistic Knowledge Services for Instruction Interpretation
Chapter in Robotics Research, Springer, vol. 2, pp. 649-664, 2018

C. Freksa, J. van de Ven,  D. Wolter (2018):
Formal representation of qualitative direction
In International Journal of Geographical Information Science published by Taylor & Francis in 2018 [Link]

Daniel Beßler, Mihai Pomarlan, Michael Beetz (2018):
OWL-enabled Assembly Planning for Robotic Agents
In Proceedings of the 2018 International Conference on Autonomous Agents, 2018

Jakob Suchan, Mehul Bhatt (2018):
Deep Semantic Abstractions of Everyday Human Activities
In ROBOT 2017: Third Iberian Robotics Conference, Springer International Publishing, Cham, pp. 477-488, 2018

J. Suchan, M. Bhatt, P. Walega, C. Schultz (2018):
Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning about Moving Objects 
In AAAI 2018: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2-7. 2018, New Orleans, USA.