Humanoid soccer stops juggling separate controllers: SoccerBot unifies four skills on a human motion prior and transfers zero-shot to a real robot
Humanoid soccer robots have either covered only a few skills or skipped motion priors entirely and moved unnaturally. SoccerBot distills large-scale human soccer motion-capture data into a structured latent motion prior, letting a single skill-conditioned policy learn moving, dribbling, trapping and kicking in one latent space. On the Unitree G1, the policy transfers zero-shot to hardware, with simulation success rates of 97.04% for kicking and 89.88% for dribbling, while real-robot kicking direction error rises from 4.09 to 10.41 degrees.