Table tennis robot is an important assistant in table tennis players' trainings. During partner trainings, table tennis robot is designed to simulate the motion trail of table tennis by tracking its trajectory after players' batting. As for this, it is consequently of great importance for the robot to real-timely adjust its hitting position and force. In this study, the trajectory of table tennis is divided into two categories: trail tracking and trail prediction, so as to construct the region-growing tracking model and perfection model for table tennis trajectory. On this basis, by drawing support from region-growing algorithm, we are to analyze the motion trail of table tennis captured by video equipments, to simulate its trajectory and to compute the motion speed and other importance information of table tennis in different direction and time. Then, the information acquired will be taken as conductions and input into trail prediction model, so as to precisely simulate the trajectory of table tennis.
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