Global vision systems as found in the small size league are prohibited in the middle size league. This paper presents methods for creating a global view of the world by cooperative sensing of a team of robots. We develop a multiobject tracking algorithm based on Kalman filtering and a single-object tracking method involving a combination of Kalman filtering and Markov localization for outlier detection. We apply these methods for robots participating in the middlesize league and compare them to a simple averaging method. Results including situations from real competition games are presented.