The trajectory prediction and analysis of spinning ball for a table tennis robot application

Abstract

The identification and trajectory prediction of spinning ball has been a problem for years. In order to improve the accuracy of trajectory prediction we take following measures: firstly the kinematics model of the flight spinning ball is analysed; then based on the Unscented Kalman Filter (UKF), the motion equation and observation equation of the ball's movement trajectory is constructed; finally the BP pattern recognition classifier is used to recognize the pattern according to the predicted flight trajectory. Large number of Matlab simulations and experimental results show that, in comparing with that of EKF, UKF can save 99% of the computing time and also get more accurate prediction. BP classifier outperforms other similar classifiers, and is more suitable for the trajectory recognition of spinning ball movement.