Applications

Bin Picking

Bin picking is the task of extracting individual items from a container of randomly piled, often overlapping objects, a longstanding industrial challenge combining severe occlusion, unknown object poses, gripper-bin collisions, and entangled parts. Modern systems pair 3D sensing with learned grasp detection and are widely deployed in logistics piece-picking; Dex-Net and the Amazon Picking Challenge were influential in moving the field from CAD-matched parts to novel-object picking.

Why it matters for physical AI

Warehouse piece-picking is among the first high-volume commercial wins for learned grasping, and its residual failure cases, transparent packaging, entanglement, and deformables, still steer perception and gripper research.