We are interested in studying how environmental and control factors affect the performance of a homogeneous multi-robot team doing a search and retrieval task. We have constructed a group of inexpensive robots called the Minnesota Distributed Autonomous Robot Team (MinDART) which use simple sensors and actuators to complete their tasks. We have upgraded these robots with the CMUCam, an inexpensive camera system that runs a color segmentation algorithm. The camera allows the robots to localize themselves as well as visually recognize other robots. We analyze how the team's performance is affected by target distribution (uniform or clumped), size of the team, and whether search with explicit localization is more beneficial than random search.