Map-based localization using the panoramic horizon

An approach is presented to solve the localization problem, in which an observer is given a topographic map of an area and dropped off at an unknown location. The solution to this problem requires establishing correspondences between viewer-centered observable features and their location on the map. The feature selected is the panoramic horizon curve, defined as the sky-ground boundary perceived by the observer as a full 360° rotation is performed. The authors propose to extract from many locations in the map the panoramic horizon curves which would be observed by the observer at each location. Such curves are encoded and stored in a table. To locate an unknown location, the panoramic horizon curve of the unknown location is first extracted, and then approximated by a family of polygons with different line fitting tolerances. By indexing into the table, candidate locations are retrieved. The correct candidate is found by applying further geometrical constraints in the verification step. The claims are validated by showing some results from a real map