Masa tenisi robotu için makine öğrenmesi temelli top yörüngesi ve vuruş noktası tahmini yapan sistemin geliştirilmesi

This thesis study includes the method and dataset information to be used to estimate the trajectory of a ball thrown in a table tennis game. One of the most important problems for professional/semi-professional table tennis players is to find a trainer or partner who will contribute to their development. To develop skills against different playing styles, it is necessary to train with players of these styles. It is very difficult to find this opportunity in table tennis because it is less popular than other sports. To solve this problem, the development of table tennis robots for years has been the subject of research since the late 1980s and dozens of studies have been carried out in this field. Common problems for all methods; is to find the appropriate stroke point, racket trajectory, stroke rate, and angle for the table tennis robot that hits the ball well. In these methods, the main goal is to get the trajectory prediction at the right time. As the ball flight time can be under 200 ms for an attacking player, the trajectory prediction must end under 100 ms. The fact that there is no definitive solution to this problem in studies conducted with different methods reveals the necessity of the prediction algorithm to be more economical and time-sensitive. With this research, the most economical method and dataset structure that this method will work on will be designed by examining the methods in the existing studies.