Camera pose and spatial arrangement are the most important dimensions for both collecting diverse robot data and retrieving useful subsets, and aligned retrieval from DROID beats full-dataset co-training on real tasks.
In total, there are∼290 unique task instances in each lab, with skill-level overlap designed to test positive retrieval strategies
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What Matters in Learning from Large-Scale Datasets for Robot Manipulation
Camera pose and spatial arrangement are the most important dimensions for both collecting diverse robot data and retrieving useful subsets, and aligned retrieval from DROID beats full-dataset co-training on real tasks.