Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation

Equivariant Descriptor Fields (EDFs) [61] achieve dataefficient end-to-end learning on 6-DoF visual robotic manipulation Diffusion generative modeling has become a promising tasks by employing SE(3) bi-equivariant [37, approach for learning robotic manipulation tasks 61] energy-based models. However, EDFs require more from stochastic human demonstrations. In this paper, than 10 hours to learn from only a few demonstrations due we present Diffusion-EDFs, a novel SE(3)-equivariant to the inefficient training of energy-based models.