Design, Modeling, and Experimental Validation of a Vision-Based Table Tennis Juggling Robot

Abstract

This paper develops a new vision-based robot customized for table tennis juggling tasks. Specifically, the robot is equipped with two industrial cameras operating as a sensing system. An image-processing algorithm is proposed that allows the robot to balance a table tennis ball while controlling its bounce height. The robot adopts a parallel structure design, and the end effector employs three ball joints to increase the degree of freedom (DOF) of the parallel mechanism. In addition, we design a control scheme explicitly customized for this robotic system. Extensive real-time experiments are performed to show the effectiveness of the juggling robot at different jumping heights. Furthermore, the ability to consistently maintain a fixed preset bounce height is demonstrated. These experimental results confirm the efficacy of the developed robotic system.