PFM-HR：面向人形机器人的位姿流匹配
Original title: PFM-HR: Pose Flow Matching for Humanoid Robots
ResearchAI 90
Source: arXiv cs.ROPublish time unverified
arXiv:2608.03227v3 Announce Type: replace Abstract: Motion priors improve reinforcement learning for physics-based humanoid tracking, but temporal priors require ordered motion clips, while pose priors provide limited guidance for policy-induced pose transitions. We present Pose Flow Matching for Humanoid Robots (PFM-HR), a reusable flow matching prior trained directly on large scale unordered pose data.