Ball juggling robot system controlled by high-speed vision

Abstract

As an example of human-like dynamic manipulation, robotic juggling using simple end effectors has been studied. The purpose of this research is to achieve juggling with a multifingered hand and arm like those of a human. One serious problem is that the weight of a multi-fingered hand and arm is large, and it is necessary to optimize the movement of the arm in order to compensate for the weight of the hand. In this paper, we propose a method of optimizing the motion trajectory using a smoothing spline. Parameters of the smoothing spline are optimized offline using a genetic algorithm. Another problem is to catch a falling ball accurately by the multifingered hand, and we use a high-speed vision system to estimate the trajectory of the ball. The task to be performed online by the robot hand and arm is to use the optimized parameters to throw a ball up into the air and catch the falling ball with high-speed visual feedback, repeatedly. We show the effectiveness of the proposed method by experiments in which the hand and arm realized throw-up and catch motions seven consecutive times.