Vision for mobile robot localization in urban environments

This paper addresses the problem of mobile robot localization in urban environments. Typically, GPS is the preferred sensor for outdoor operation. However, using GPS-only localization methods leads to significant performance degradation in urban areas where nearby tall structures obstruct the clear view of the satellites. In our work, we use vision-based techniques to supplement GPS and odometry and provide accurate localization. The vision system identifies prominent linear features in the scene and matches them with a reduced model of nearby buildings, yielding improved pose estimation of the robot.