Ψ 0 Ψ_0 Ψ0: An Open Foundation Model Towards Universal Humanoid Loco-Manipulation

This paper introduces an open foundation model for universal humanoid loco-manipulation. It employs a decoupled learning strategy that first pre-trains on human egocentric videos to acquire generalizable visual-action representations, and then post-trains on significantly less robot data for precise joint control. This approach achieves over 40% higher success rates on complex, long-horizon tasks compared to state-of-the-art baselines and demonstrates improved data efficiency, paving the way for more capable humanoid robots.