Visual Homing is a bioinspired approach to robot navigation which can be fast and uses few assumptions. However, visual homing in a cluttered and unstructured outdoor environment offers several challenges to homing methods that have been developed for primarily indoor environments. One issue is that any current image during homing may be tilted with respect to the home image. The second is that moving through a cluttered scene during homing may cause obstacles to interfere between the home scene and location and the current scene and location. In this paper, we introduce a robust method to improve a previous developed Homing with Stereo Vision (HSV) method for visual homing. HSV adds stereo information to the image information typically used in homing resulting in improved performance. The Robust Homing with Stereo Vision (RHSV) algorithm is modified to deal with current images taken at arbitrary pitch and roll values, and to handle homing and navigation through occluding obstacles. The results for several trials comparing HSV and RHSV are presented and the future direction of this work outlined.