AIBullisharXiv – CS AI · 8h ago7/10
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CoRe-MoE: Contrastive Reweighted Mixture of Experts for Multi-Terrain Humanoid Locomotion with Gait Adaptation
Researchers introduce CoRe-MoE, a reinforcement learning framework enabling humanoid robots to seamlessly transition between walking and running while adapting to complex terrains. The two-stage approach decouples gait generation from terrain adaptation using a contrastive learning mechanism, with successful zero-shot deployment on a Unitree G1 robot across varied outdoor environments.