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Tutorial on CRAM

The video is a tutorial showing the basics of the CRAM framework, which is a toolbox for designing, implementing, and deploying software on autonomous robots. The aim of the tutorial is to (1) give an intuition of what knowledge the robot needs to execute even a simple fetch and place, (2) show how many different things can go wrong and teach writing simple failure handling strategies, and (3) make the user familiar with the API of the actions already implemented in the CRAM framework.


Gayane (shortly Gaya) is a PhD student at the Institute for Artificial Intelligence of the University of Bremen. Her main research interests are concentrated in the area of cognition-enabled robot executives. She is currently actively and passionately involved in the development of CRAM. Before joining Michael Beetz's group in November 2013, she worked for one year as a research assistant at Kastanienbaum GmbH (now Franka Emika) with Sami Haddadin, in tight collaboration with the Robotics and Mechatronics Center of DLR. Before that, she has acquired her M.Sc. degree in Informatics with a major in AI and Robotics at the Technical University of Munich. Before coming to Germany, she had a number of short-term jobs in the fields of iPhone game development and web development. She's got her B.Eng. degree in Informatics with a major in Information Security from the State Engineering University of Armenia.

Lecture Video