Stereo vision for small mobile robots is a challenging problem, particularly when employing embedded systems with limited processing power. However, it holds the promise of greatly increasing the localization, mapping, and navigation ability of mobile robots. To help in scene understanding, objects in the field of vision must be extracted and represented in a fashion useful to the system. At the same time, methods must be in place for dealing with the large volume of data that stereo vision produces, in order that a practical frame rate may be obtained. We have been working on stereo vision as the sole form of perception for Urban Search and Rescue (USAR) domains over the last three years. Recently, we have extended our work to include domains with more complex human robot interactions. Our entry in the 2006 AAAI Robotics competition embodies these ideas.