EAGG introduces a grasp generator that aligns embodiment structure within a shared model using topology-aware graphs and geometry-aware tokens. It achieves 56.17% average grasp success on MultiGripperGrasp, matching specialized models within 1.10 percentage points and reducing median contact distance from 0.239 cm to 0.189 cm.
arxiv
arXiv cs.AI
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53d ago
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research
EAGG: Embodiment-Aligned Grasp Generation via Geometry-Aware Graph Conditioning
from English
Importance 2/3
New harness with differentiators
arXiv cs.AI
Microsoft Research
Allen AI
Hugging Face
AI agents
Evaluation & benchmarks
Robotics
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