ZiF Research Group

Cognitive Behavior of Humans, Animals, and Machines:

Situation Model Perspectives

October 2019 – July 2020

Convenors: Werner Schneider (Bielefeld, GER), Helge Ritter (Bielefeld, GER)

Michael Beetz

Associate Fellow

Foto Collaborative Resaerch Centre ''Everyday Activity Science
and Engineering'' (EASE), &
Institute for Artificial Intelligence, Department of Informatics,
University of Bremen, Germany
E-Mail: beetz@cs.uni-bremen.de


Michael Beetz is a professor for Computer Science at the Faculty for Mathematics & Informatics of the University of Bremen and head of the Institute for Artificial Intelligence (IAI). He received his diploma degree in Computer Science with distinction from the University of Kaiserslautern. His MSc, MPhil, and PhD degrees were awarded by Yale University in 1993, 1994, and 1996, and his Venia Legendi from the University of Bonn in 2000. In February 2019 he received an Honorary Doctorate from Örebro University.
Michael Beetz is coordinator of the German collaborative research centre EASE since 2017 and co-coordinator of the University of Bremen research focus area ''Minds, Media, Machines''. He was vice-coordinator of the German cluster of excellence CoTeSys (Cognition for Technical Systems, 2006-2011) and coordinator of the European FP7 integrating project RoboHow (web-enabled and experience-based cognitive robots that learn complex everyday manipulation tasks, 2012-2016).

Current Main Research Interests

My research interests include plan-based control of robotic agents, knowledge processing and representation for robots, integrated robot learning, and cognition-enabled perception.

Through my research I want to understand the information processing principles that enable robotic agents to perform the appropriate actions with the appropriate objects in the appropriate ways when given vague instructions such as ''make me two eggs sunny-side up'' or ''provide the isolated disaster victims in the harbor area with the necessary emergency supplies''. I have been fascinated by, and working towards, this research challenge since the beginning of my academic career. I believe that improving our understanding of these principles is essential for the development of robot assistants that will enable many people in our aging societies to live more independently and improve their quality of life.

Five selected publications with particular relevance to the Research Group
  • Ramirez-Amaro, K., Beetz, M., & Cheng, G. (2017). Transferring skills to humanoid robots by extracting semantic representations from observations of human activities. Artificial Intelligence, 247, 95-118.
  • Tenorth, M., & Beetz, M. (2017). Representations for robot knowledge in the KnowRob framework. Artificial Intelligence, 247, 151-169.
  • Leidner, D., Dietrich, A., Beetz, M., & Albu-Schäffer, A. (2016). Knowledge-enabled parameterization of whole-body control strategies for compliant service robots. Autonomous Robots, 40, 519-536.
  • Tenorth, M., & Beetz, M. (2013). KnowRob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research, 32, 566-590.
  • Beetz, M., Jain, D., Mosenlechner, L., Tenorth, M., Kunze, L., Blodow, N., & Pangercic, D. (2012). Cognition-enabled autonomous robot control for the realization of home chore task intelligence. Proceedings of the IEEE, 100, 2454-2471.