P-BFM: Perceptive Behavioral Foundation Models for Humanoid Control
Overview
P-BFM uses unsupervised reinforcement learning to enable humanoids to adapt motions to different terrains without specific demonstrations, improving motion fidelity and recovery across challenging environments. It supports zero-shot transfer using onboard depth sensing.
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- arXiv Robotics — research abstractsP-BFM: Perceptive Behavioral Foundation Models for Humanoid Control via Unsupervised Reinforcement Learning
P-BFM is a behavioral foundation model that enables humanoids to adapt their motions to different terrains by separating global transport from behavioral intent. It uses unsupervised reinforcement learning to generate terrain-appropriate behaviors without terrain-specific demonstrations, improving motion fidelity and recovery across challenging terrains. The model supports zero-shot transfer to new platforms using onboard depth sensing.
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