Service robots will have to accomplish more and more complex, open-ended tasks and regularly acquire new skills. In this work, we propose a new approach to generating plans for such household robots. Instead composing them from atomic actions, we propose to transform task descriptions on web sites like ehow.com into executable robot plans. We present methods for automatically converting the instructions given in natural language into a formal, logic-based representation, for resolving the word senses using the WordNet database and the Cyc ontology, and for exporting the generated plans into the mobile robot’s plan language RPL. We discuss the problems of inferring information in these descriptions, of grounding the abstract task descriptions in the perception and action system, and we propose techniques for solving them. The whole system works autonomously without human interaction. It has successfully been tested with a set of about 150 natural language directives, of which up to 8...