Antoni Planells

A friction-model-based framework for Reinforcement Learning of robotic tasks in non-rigid environments

Learning motion tasks in a real environment with deformable objects requires not only a Reinforcement Learning (RL) algorithm, but also a good motion characterization, a preferably compliant robot controller, and an agent giving feedback for the rewards/costs in the RL algorithm. In this paper, we u…