Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning

arXiv:2606.28813v1 Announce Type: new Abstract: Human videos are a scalable source of supervision for robot manipulation, as they are abundant and naturally capture rich object interactions. However, transferring human demonstrations to robots remains challenging due to embodiment mismatch, scene variation, and robot-specific feasibility constraints. We present Human2Any, a framework for learning reusable object-centric interaction priors from human videos without requiring real-world robot demo...