Abstract
In table tennis the rotation (spin) of the ball plays a crucial role. A table tennis match will feature a variety of strokes. Each generates different amounts and types of spin. To develop a robot which can compete with a human player, the robot needs to be able to detect spin, so that it can plan an appropriate return stroke. In this paper we compare three methods for estimating spin. The first two approaches use a high-speed camera that captures the ball in flight at a frame rate of 380 Hz. This camera allows the movement of the circular brand logo printed on the ball to be seen. The first approach uses background difference to determine the position of the logo. In a second alternative, a CNN is trained to predict the orientation of the logo. The third method evaluates the trajectory of the ball and derives the rotation from the effect of the Magnus force. In a demonstration, our robot must respond to different spin types in a real table tennis rally against a human opponent.
Abstract (translated by Google)
URL
http://arxiv.org/abs/1905.07967