#Motion Latents (1)

VioLA: Learning Generalist Humanoid Control Policies from Human Data

VioLA is a generalist humanoid policy that predicts body and hand motion latents instead of joint commands. Frozen SONIC-based encoders map human and robot demonstrations into the same action space, so 93.2% of its 140.6M training frames come from human recordings. On a real Unitree G1 it reaches 100% locomotion and 88.6% manipulation success with no task-specific fine-tuning.