INTEGRATION OF ORBITAL AND GROUND IMAGE NETWORKS FOR THE AUTOMATION OF ROVER LOCALIZATION

Rover localization is essential to the exploration of space. The availability of sub-meter resolution satellite imagery, especially HiRISE imagery, has opened the possibility of computing rover locations at higher accuracy by making use of detailed features seen in the satellite orbital images. This paper describes a new development towards automation of the rover localization process using orbital and ground images. Using a rigorous sensor model and bundle adjustment (BA) of HiRISE stereo imagery, high-resolution orthophotos and DEMs can be generated as soon as the orbital stereo images are acquired. A ground image network is also constructed using intra- and inter-stereo matching. From both types of imagery, a few landmarks are identified to be used as ground control points for the integration of the orbital and ground image networks. Rocks detected from both orbital and ground imagery serve as tie points for rover localization. From orbital images, rocks are extracted based on brightness values and the shape of dark spots. Rocks in ground images are extracted through dense stereo matching, rock peak and surface point extraction, and rock modeling. To narrow down a precise rover position, terrain match is performed using DEMs generated from orbital and ground imagery. Finally, distribution pattern matching is implemented for rocks detected from orbital and ground imagery. The rover position is adjusted based on 2D affine transformation obtained from rock pattern matching. The proposed method has been tested for the Spirit rover traverse. Experimental results show that the orbital/ground rock matching approach has performed successfully for MER rover localization