Maximum likelihood rover localization by matching range maps

This paper describes maximum likelihood estimation techniques for performing rover localization in natural terrain by matching range maps. An occupancy map of the local terrain is first generated using stereo vision. The position of the rover with respect to a previously generated occupancy map is then computed by comparing the maps using a probabilistic formulation of image matching techniques. Our motivation for this work is the desire for greater autonomy in Mars rovers. These techniques have been applied to data obtained from the Sojourner Mars rover and run on-board the Rocky 7 Mars rover prototype