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Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intelligence. Employing this approach enables robots to reason about how to solve tasks in dynamic environments and to adapt to unseen situations.

Autonomous systems --- Graphical programming --- Humanoide Robotik --- Programming by demonstration --- Autonome Systeme --- Robotik --- Programmieren durch Vormachen --- Robotics --- Humanoid robotics --- Graphische Programmierung