This thesis describes a method to create local maps from an omni-directional vision system (ODVS) mounted on a mobile robot. Range finding is performed by a structure-from-motion method, which recovers the three-dimensional position of objects in the environment from omni-directional images. This leads to map-making, which is accomplished using certainty grids to fuse information from multiple readings into a two-dimensional world model. The system is demonstrated both on noise-free data from a custom-built simulator and on real data from an omni-directional vision system on-board a mobile robot. Finally, to account for the particular error characteristics of a real omni-directional vision sensor, a new sensor model for the certainty grid framework is also created and compared to the traditional sonar sensor model.