Cooperative suspended object manipulation using reinforcement learning and energy-based control

Cooperative dynamic object manipulation can extend the manipulation capabilities of robot-robot and human-robot teams. In order to be able to inject energy into various suspended objects of unknown parameters, in this paper we propose an adaptive controller which combines reinforcement learning with energy based swing-up control. The proposed controller is successfully verified in a single robot and human-robot experimental setup for different types of suspended objects.