Solving the Rubik’s Cube with a Robot Hand
We’ve trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand.
The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR).
Handling Unseen Situations
The system can handle situations it never saw during training, such as being prodded by a stuffed giraffe.
This shows that reinforcement learning isn’t just a tool for virtual tasks, but can solve physical-world problems requiring unprecedented dexterity.