SeededGrasp splits language reasoning from grasp generation and hits 78% real-world success
Yang Xu · hf · 2026-07-23
SeededGrasp is a language-guided grasping framework for complex scenes that separates semantic reasoning from geometric execution.
- A VLM predicts a seed point from the language instruction.
- A lightweight grasp-generation model then uses that seed to produce the final grasp, avoiding expensive end-to-end training.
- The authors release the first multi-embodiment tabletop grasping dataset, with more than 2.5M grasps in cluttered scenes.
- Results show 72% success in simulation and 78% in real-world experiments, outperforming prior baselines.
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