Visual Measurement and Prediction of Ball Trajectory for Table Tennis Robot

Abstract

A high-speed stereovision system with two smart cameras is presented to track a table tennis ball, which adopts a distributed parallel processing architecture based on a local area network. A set of novel algorithms with little computation and good robustness running in the smart cameras is also proposed to recognize and track the ball in the images. A computer receives the image coordinates of the ball from the cameras via the local area network and computes its 3-D positions in the working frame. Then, the flying trajectory of the ball is estimated and predicted according to the measured positions and the flying and rebound models. The main motion parameters of the ball such as the landing point and striking point are calculated from its predicted trajectory. Experimental results show that the developed image-processing algorithms are robust enough to distinguish the ball from a complex dynamic background. The predicted landing point and striking point of the ball have satisfactory precision.