Pre-training Visual Dexterity in Simulation

Key points

Using VR teleoperation in simulation, it collected 75 hours of hand-manipulation data, approximately 2000 episodes, in one week without a real robot.
After pretraining, fine-tuning on just 1–2 hours of real demonstrations outperformed training from scratch on all 5 real-world tasks.
Providing a history of past observations and using short action chunks of 8 steps achieved both responsiveness and consistency.
The configuration combining history with short action chunks benefited most from pretraining, improving by an average of 18 points over training from scratch.
It released the dataset (spd-75h), VR collection software (spd-vr), and 6 tuned scenes.

External research summaries. These are not HDATF publications or measured product results.