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However, in many current robotics datasets there is an uneven distribution of scenes and demonstrations.

The framework works by producing synthetic visual demonstrations that vary in both robot punch in and camera angles.

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This allows researchers to train robots on a wider range of demonstrations, enabling more efficient skill transfer.

Candidate, AUTOLab, EECS & IEOR, BAIR, UC Berkeley) and Chenfeng Xu (Ph.D. ## You might also like