A possible model to explain the symbol grounding problem is the DIKW pyramid. Grounding means to translate a higher layer in the pyramid into a lower layer. The layers are representating the same reality in different formats. The perhaps most important transition is from the numerical data layer into the labeled data. For a warehouse robot a GPS sensor reading like (40,10) gets translated into [roomB]. So the low level sensor data gets annotated with tag.
The next layer is the knowledge graph which encodes the tagging information into a semantic network. The realations between the tags are explained, synonyms are introduced and the information are stored in a json file. If all the layers in the DIKW pyramid are established and if an automatic parser can translate upward and downward in the pyramid, its possible to communicate with a robot in natural language. A voice command like "go to roomB and bring me the yellow box" is understood by the robot and executed in the reality.
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