CDPs add a simple contraction regularizer to diffusion policies, pulling nearby sampling trajectories together to suppress solver and score-matching errors. This yields more robust action generation in offline RL and imitation learning, especially in low-data regimes.

VOCALoco predicts the viability and cost of transport for several pretrained locomotion skills from local heightmaps, then executes the safest, most efficient one. It improves robustness on stairs and transfers zero-shot to real hardware.