A Novel Trajectory-Based Ball Spin Estimation Method for Table Tennis Robot.

Sport and game industry has grown rapidly in recent years due to the application of novel sensors and algorithms for quantitative analysis. For example, flying speed and spin estimation is essential to help players to improve their skills in table tennis. However, the spin estimation for a table tennis ball is challenging, as it is difficult to observe using cameras and model the aerodynamics of ball flight with spin. This article proposes a generalized aerodynamic model with variable aerodynamic coefficients to accurately represent the flying state of a table tennis ball. Analytical solutions for the aerodynamic coefficients and the acceleration due to the Magnus force are also developed for accurate ball spin estimation using pre- and postrebounding flight trajectories. The experimental results showed that compared to current state-of-the-art methods, the proposed method has achieved the best performance in angular velocity magnitude estimation for topspinning and backspinning balls. It also achieved an error of below 10° in angular velocity amplitude estimation. Using the proposed spin estimation method, our table tennis robot could strike balls with either topspin or backspin with a high success rate of up to 84.6 $%$ . Besides, the experimental results also demonstrated the potential of the proposed method in the area of table tennis training and sports-broadcasting.