A single diffusion-plus-residual-RL policy, trained on four robot morphologies using zero-padded observations and actions, outperforms per-robot PPO baselines in simulation and transfers to real robots.
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Multi-Loco: Unifying Multi-Embodiment Legged Locomotion via Reinforcement Learning Augmented Diffusion
A single diffusion-plus-residual-RL policy, trained on four robot morphologies using zero-padded observations and actions, outperforms per-robot PPO baselines in simulation and transfers to real robots.