Abstract
This paper is motivated by the goal of a visual perception system for the RoboCup 2050 challenge to win against the human world-cup champion. Its contribution is to answer two questions on the subproblem of predicting the motion of a flying ball. First, if we could detect the ball in images, is that enough information to predict its motion precise enough? And second, how much do we lose by using the real-time capable Unscented Kalman Filter (UKF) instead of non-linear maximum likelihood as a gold standard? We present experiments with a camera and an inertial sensor on a helmet worn by a human soccer player. These confirm that the precision is roughly enough and using an UKF is feasible.
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Birbach, O., Kurlbaum, J., Laue, T., Frese, U. (2009). Tracking of Ball Trajectories with a Free Moving Camera-Inertial Sensor. In: Iocchi, L., Matsubara, H., Weitzenfeld, A., Zhou, C. (eds) RoboCup 2008: Robot Soccer World Cup XII. RoboCup 2008. Lecture Notes in Computer Science(), vol 5399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02921-9_5
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DOI: https://doi.org/10.1007/978-3-642-02921-9_5
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