Online angular velocity estimated visual measurement for ping pong robot
ZHANG Yuan-hui1,2,WEI Wei2
1. College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China;
2. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Currently, the failure of precisely identifying and tracking the spin ball trajectory in ping pong robot's vision system leads to large errors in the predicting result. Aiming at the problem, an online nonlinear Kalman filter based visual measurement method was proposed to estimate the angular velocity. Aerodynamics theory was applied to analyze the forces acting on the spin ball. The motion equation and observation equation of the trajectory were constructed, and the nonlinear extended Kalman filter was integrated to estimate the motion states involving the angular velocity. Both simulation and actual experiments verified the effectiveness and correctness of the method. The prediction result outperformed other tracking methods. The method can also be employed in the high-speed motion tracking conditions．
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