Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

Understand

Imitation learning is a powerful paradigm for robot skill acquisition.

• However, obtaining demonstrations suitable for learning a policy that maps from raw pixels to actions can be challenging.
• In this paper we describe how consumer-grade Virtual Reality headsets and hand tracking hardware can be used to naturally teleoperate robots to perform complex tasks.
• We also describe how imitation learning can learn deep neural network policies (mapping from pixels to actions) that can acquire the demonstrated skills.