Watch their moves: applying probabilistic multiple object tracking to autonomous robot soccer

Abstract

In many autonomous robot applications robots must be capa-ble of estimating the positions and motions of moving objects in their environments. In this paper, we apply probabilistic multiple object tracking to estimating the positions of oppo-nent players in autonomous robot soccer. We extend an exist-ing tracking algorithm to handle multiple mobile sensors with uncertain positions, discuss the specification of probabilistic models needed by the algorithm, and describe the required vision-interpretation algorithms. The multiple object track-ing has been successfully applied throughout the RoboCup 2001 world championship.