This paper proposes a spatial language generation system to communicate with a person about the location of an object in an indoor environment. It aims at finding a short, accurate and human-like description for building a natural and friendly interface between robots and humans using spatial language interaction. The system performs an inverse procedure to spatial language grounding which links natural commands to robot actions. The system works in two steps. It will first search for the best matching grounding model which describes the spatial relations between the target object and the references; then it will generate the natural language by mimicking a human's talking style. A corpus of 149 spatial language commands for an indoor environment fetch task is used to train the language generation model. An early-stage experiment is conducted and the results illustrate a potential for further development.
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