RetrDex: Efficient Object Retrieval in Cluttered Scenes with a Dexterous Hand

Understand

Retrieving objects buried beneath clutter is both challenging and time-consuming, as complex support relationships make manipulation particularly difficult.

• Existing methods either focus on support relations and rely on sequential grasping to remove occluding objects, or perform preparatory actions such as pushing to facilitate subsequent grasps.
• However, these approaches are often inefficient and treat physical interactions as isolated auxiliary steps.
• In this paper, we propose RetrDex, an efficient framework for dexterous arm-hand systems to learn object retrieval in cluttered scenes.