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HOLA enables robot teams to seamlessly adapt to new environments and partners, outperforming traditional methods in dynamic settings.
DREAM-Chunk transforms action chunking by leveraging latent world models to enhance robustness against stochastic dynamics without the need for policy retraining.
Achieve model-free RL sample efficiency with model-based control performance by sidestepping multi-step rollout errors via one-step Koopman dynamics predictions.
Ditch slow nonlinear dynamics for control: a learned linear Koopman operator speeds up MPPI while maintaining performance.
