WorldDreamer: World Models for Robot Learning

摘要

We introduce WorldDreamer, a world model approach for robot learning and manipulation. WorldDreamer learns an internal world model that can predict the consequences of robot actions, enabling model-based planning and imagination-based learning. The approach allows robots to learn manipulation skills through mental simulation, reducing the need for extensive real-world interaction data.