Erik Kyrkjebø

Combining exploration and imitation in contact-rich task learning on an articulated soft robot arm

This study investigates the combination of a state-of-the-art reinforcement learning (RL) algorithm with human demonstrations to learn how to open a door with minimal task-specific engineering on an articulated soft robot arm and shows that combining LfD with RL results in both better performance and more robust behaviors.