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G1 Brunson: Humanoid Robot Between-the-Legs Dribbling Control Based on Deep Visual Reinforcement Learning

G1 Brunson uses event-based rewards and asymmetric actor-critic training, bringing the depth camera directly into the observation loop during training to form a G1 whole-body dribbling policy. Reproducing the official weights locally in MuJoCo gave an average of 43.5 crossovers over 12 episodes with zero falls, matching the official results.

Part of the event: G1 achieves between-the-legs dribbling with deep vision reinforcement learning

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