Sobolev-trained diffusion policies using trajectories and feedback gains provide warm-starts that reduce trajectory optimization solving time by 2x to 20x while avoiding compounding errors.
In: 9th Inter- national Conference on Learning Representations, ICLR 2021 (2021)
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Accelerating trajectory optimization with Sobolev-trained diffusion policies
Sobolev-trained diffusion policies using trajectories and feedback gains provide warm-starts that reduce trajectory optimization solving time by 2x to 20x while avoiding compounding errors.