Rover localization in natural environments by indexing panoramic images

In this paper, we present an approach to qualitative rover localization with panoramic images. The approach relies on the possibility to efficiently and robustly compute the resemblance between panoramic images, indexing them by histograms of local appearances. A database of image indexes is dynamically built during rover motions: when the rover re-perceives an already crossed area, it matches the current image with the stored ones (place recognition), and thus gets a qualitative estimate of its position. Experimental results on a 400 images database illustrates the effectiveness of the algorithms.