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Humanoid robots can now sprint at 6 m/s with zero-shot sim-to-real transfer, thanks to a surprisingly data-efficient approach using frequency-domain priors learned from just five human motion sequences.
Imagine controlling a robotic dog with simple voice commands, instantly switching between complex skills like obstacle avoidance and object manipulation.
Ditching depth sensors, GeoLoco achieves robust zero-shot sim-to-real humanoid locomotion from RGB images alone by cleverly encoding 3D geometric priors from a visual foundation model.
