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RodForesight: A World Model Enhanced Diffusion Policy for Slender Rod Insertion
Slender rod insertion arises in precision manufacturing, where millimetre scale diameter and tight clearances demand accurate perception and control. Conventional peg-in-hole methods assume a rigid object whose tip pose is fixed relative to the gripper. This assumption breaks down for a high aspect ratio rod, which can bend during manipulation, making its tip motion dependent on the rod configuration, grasp, material properties, and contact. We present RodForesight, a learning framework that factorises the task into two stages: 1) coarse approaching, which uses visual servoing to map diverse i
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T18:31:55.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.