With the robotics development, social robots interact with people, demanding they model the human being behavior to increase social navigation, considering proxemic spaces. However, human proxemic preferences can change in function of different social restrictions (e.g., culture, gender, local, the environment). Thus, robots should consider all these aspects to tailor their navigation. Towards an adaptable social navigation, in this article we develop the GProxemic Navigation system that allows identifying the robot localization in a geo-referenced map, with semantic annotations related to social restrictions, in function of which they chose the correct proxemic spaces they most respect in their autonomous navigation process. Results show that the GProxemic Navigation system efficiently obeys the proxemic space through the semantic annotations received.