Trajectory Prediction of Spinning Ball Based on Fuzzy Filtering and Local Modeling for Robotic Ping–Pong Player

In this paper, a novel prediction method of the striking position is proposed for a robotic ping-pong player. In order to remove the noise involved in the coordinates of ping-pong ball, a new nonlinear filter based on fuzzy logic approach is presented. Then, least square method (LSM) is utilized to compute the initial flying and rotational velocities based on the filtered positions of the ball. The impact between a ping-pong ball and the table is studied, and the analytic model that represents the relationship between the velocities before and after rebound is developed. Based on statistical analysis, a memory-based local modeling approach is presented to obtain a more accurate velocity after rebound. The succeeding trajectory is predicted according to the initial state of the ball and the flying and rebound models. The striking position can be obtained from the predicted trajectory. Experiments are well conducted and verify that sufficient precision of the striking position have been achieved with the proposed method.