Manipulation

Deformable Object Manipulation

Deformable Object Manipulation is the robotic handling of objects that change shape under contact, including cloth, cables, bags, and food items. It is challenging because the object state is effectively infinite-dimensional, self-occlusion complicates perception, and dynamics are difficult to model or simulate accurately. Benchmarks such as SoftGym and tasks like cloth folding, rope routing, and bag opening drive research combining learned dynamics models, dense visual correspondence, and imitation learning.

Why it matters for physical AI

A large share of household, hospital, and logistics work involves laundry, cables, packaging, and food rather than rigid parts. Progress on deformables is therefore a gating factor for general-purpose robots leaving structured industrial settings.