InterMimicGen: Scaling Humanoid Loco-Manipulation through Self-Evolving Motion Imitation

InterMimicGen utilizes a self-evolving framework to scale humanoid loco-manipulation by iteratively improving robot motion data and tracking policies. The method retargets sparse human-object interaction datasets into diverse humanoid reference collections that preserve whole-body coordination and dexterous hand-object relationships within physics-based simulations.