Location Recognition Using Stereo Vision
A mobile robot must be able to determine its own position in the world. To support truly autonomous navigation, we present a system that builds and maintains its own models of world locations and uses these models to recognize its world position from stereo vision input. The system is designed to be robust with respect to input errors and to respond to a gradually changing world by updating the world location models. We present results from tests of the system that demonstrate its reliability. The model builder and recognition system fit into a planned world modeling system that we describe.