Research and analysis of table tennis movement trajectory prediction model based on deep learning

With the development of artificial intelligence and robotics technology, the research and development of table tennis robots can help athletes to practice table tennis as partners, and can also serve as intelligent coaches for professional guidance. The key problem of the development of table tennis robot is the trajectory prediction of table tennis and the prediction of the ball point in the movement. Through the detection, analysis and modeling of the table tennis trajectory in the movement, the movement trajectory is predicted, and then helps the athletes to find out the counterattack strategy through data analysis, so as to carry out deeper tactical training. The main research content of this paper is to build the table tennis trajectory prediction model, first detect the table tennis detection and track the data set, and then establish the table tennis movement trajectory prediction network through LSTM. After the experimental data analysis, the method of this paper can get more accurate prediction results.