Manipulation

Cable Manipulation

Cable manipulation is the robotic handling of deformable linear objects such as cables, ropes, and wires, including tasks like routing, untangling, knot tying, and connector insertion. Because cables have infinite-dimensional state and complex friction dynamics, classical rigid-body planners fail, and modern approaches rely on learned dynamics models, visual tracking of keypoints, or end-to-end imitation learning. It is a canonical benchmark for deformable object manipulation research.

Why it matters for physical AI

Cables appear everywhere in manufacturing, e-commerce, and household settings, and their unpredictable dynamics make them a stress test for learned policies that must generalize beyond rigid objects.