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1,000 hours of human touch data unlocks a 37% jump in vision-only dexterous manipulation success, revealing touch as a powerful pretraining signal beyond its direct use in policies.
RoboDojo reveals that integrating simulation and real-world tasks can significantly enhance the evaluation of robot manipulation policies, bridging the gap between theoretical performance and practical deployment.