Generative Robot Data

Using generative models (diffusion models, NeRF, video prediction) to synthesize additional robot training data beyond what is physically collected. Generated data can augment rare scenarios, novel object appearances, or failure cases. Quality of generated data matters — poorly generated data can harm performance. This is an active research area for data-efficient robot learning.