Abstract

The state of arts for table tennis robot is introduced. Then a binocular stereovision vision system and related algorithm are proposed including the image processing to find the ball and the trajectory prediction model. The vision system is integrated with two smart cameras and used to track table tennis ball. The system adopts a distributed parallel processing architecture based on 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 local area network and computes its 3D 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 landing point and striking point are calculated from its predicted trajectory. The motion planning of the paddle of the table tennis robot is designed. Experimental results show that the developed image processing algorithms are robust enough to distinguish the ball from complex dynamic background. The predicted landing point and striking point of the ball have satisfactory precision. The robot can strike the ball to the semi-table at opponent side successfully.