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Found 4 papers, 3 papers with code
DayDreamer: World Models for Physical Robot Learning
Learning a world model to predict the outcomes of potential actions enables planning in imagination, reducing the amount of trial and error needed in the real environment.
RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning
Replicating human-like dexterity in robot hands represents one of the largest open problems in robotics.
Masked Trajectory Models for Prediction, Representation, and Control
We introduce Masked Trajectory Models (MTM) as a generic abstraction for sequential decision making.
Interactive Task Planning with Language Models
An interactive robot framework accomplishes long-horizon task planning and can easily generalize to new goals or distinct tasks, even during execution.
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