Robotic juggling by iterative learning control using optimization

This paper proposes the control strategy for throwing as one of the dynamic manipulation. In dynamic manipulation, the robot's motion is dynamic and quick and there is no constant contact state. The dynamic manipulation has strong nonlinearity between control input and output, which often makes the manipulation unstable. And modeling errors affect the success of its manipulation task seriously. The dynamic manipulation requires more powerful actuator than the static manipulation.We propose the control method using the learning control that can consider the modeling error problem, the performance limits of the actuator and the stability of the learning control.