Generating Grammars for Natural Language Understanding from Knowledge about Actions and Objects

abstract

Many applications in the fields of Service Robotics and Industrial Human-Robot Collaboration, require interaction with a human in a potentially unstructured environment. In many cases, a natural language interface can be helpful, but it requires powerful means of knowledge representation and processing, e.g., using ontologies and reasoning. In this paper we present a framework for the automatic generation of natural language grammars from ontological descriptions of robot tasks and interaction objects, and their use in a natural language interface. Robots can use it locally or even share this interface component through the RoboEarth framework in order to benefit from features such as referent grounding, ambiguity resolution, task identification, and task assignment.