Prior Reinforce adapts a few demonstration motions to new goals in dynamic manipulation by learning a diffusion motion prior and refining a low-dimensional condition via Bayesian optimization, reaching new goals in under 10 real trials.
UMI on legs: Making manipulation policies mobile with manipulation-centric whole-body controllers,
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Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials
Prior Reinforce adapts a few demonstration motions to new goals in dynamic manipulation by learning a diffusion motion prior and refining a low-dimensional condition via Bayesian optimization, reaching new goals in under 10 real trials.