The case for an omni-bodied robot brain

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Introduces the concept of an 'omni-bodied brain' trained on a vast simulated robot multiverse to achieve generalizable locomotion. Demonstrates in-context learning in robotics through various failure and adaptation scenarios (precarious scenarios, loss of limbs, broken legs, jammed wheels, walking on stilts), highlighting the model's ability to adapt to unseen morphological changes and environmental conditions without explicit fine-tuning.