Robotic systems operating in the real world would benefit from a clear semantic model to understand their interactions with the real world. Such semantics are typically captured in an ontology. Unfortunately, existing world models in robotics focus on its navigation task. They adopt a hierarchical structure decomposing the environment from large spaces into small objects having a position, thereby limiting the robot's interactions as a 'go-to-object' task. To allow a richer understanding of the real world this hierarchical structure should be replaced with an ontology, yet one that does not limit the real-time requirements of the robot when it is queried or updated with new observations extracted from sensors. Such an ontology is presented in this article. For now the ontology also focusses on the navigation aspect of robots, yet it is open to model other aspects of the real world as well. Experiments show that multiple environments are successfully modelled supporting the robot to go from one room to another to search for humans.