A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations

We have developed a robust qualitative method for robot exploration, mapping, and navigation in large-scale spatial environments. An environment is large-scale if its spatial structure is at a signi cantly larger scale than the sensory horizon of the observer. Experiments with a simulated robot in a variety of 2-D environments have demonstrated that our method can build an accurate map of an unknown environment in spite of substantial random and systematic sensorimotor error. Most current approaches to robot exploration and mapping analyze sensor input to build a geometric map of the environment, then extract topological structure from the geometric description.