SOURCE-LINKED INTELLIGENCE
Gripper-Aware Automatic Dense Packing of Irregular Objects
Automatic dense packing is widely desired in warehouse operations but remains a fundamental challenge in robotic manipulation. Existing work on irregular-object packing largely targets simulation with idealized contact, treating the object as an isolated rigid body. The gripper often enters as a discrete, post-hoc feasibility check, if considered at all, and the perception and contact drift accumulated during execution are not addressed. We present a closed-loop pipeline that integrates perception, gripper-aware placement optimization, and force-guided execution on a real manipulator. The opti
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T17:53:16.000Z
First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.