Cross-Domain Transfer via Semantic Skill Imitation

Understand

We propose an approach for semantic imitation, which uses demonstrations from a source domain, e.g.

• human videos, to accelerate reinforcement learning (RL) in a different target domain, e.g.
• a robotic manipulator in a simulated kitchen.
• Instead of imitating low-level actions like joint velocities, our approach imitates the sequence of demonstrated semantic skills like "opening the microwave" or "turning on the stove".