Composing Diffusion Policies for Few-shot Learning of Movement Trajectories

Understand

Humans can perform various combinations of physical skills without having to relearn skills from scratch every single time.

• For example, we can swing a bat when walking without having to re-learn such a policy from scratch by composing the individual skills of walking and bat swinging.
• Enabling robots to combine or compose skills is essential so they can learn novel skills and tasks faster with fewer real world samples.
• To this end, we propose a novel compositional approach called DSE- Diffusion Score Equilibrium that enables few-shot learning for novel skills by utilizing a combination of base policy priors.