allenaiMIT
PRISM
A large-scale synthetic dataset for task-oriented grasping featuring 379k task-grasp samples in cluttered environments with diverse task descriptions. The dataset uses 2365 object instances from ShapeNet-Sem and stable grasps from ACRONYM across 10,000 unique scenes with multiple views.
Downloads139
Episodes379000
Likes5
Why This Matters for Physical AI
PRISM provides a large-scale synthetic benchmark for training task-oriented grasp prediction models with paired natural language task descriptions, enabling research in vision-language reasoning for robotic manipulation.
Technical Profile
- Modalities
- rgbpoint_cloudsegmentationlanguage
- Environment
- simulation
- Task Types
- graspingtask-oriented-graspingmanipulation
- Episodes
- 379000
- Data Format
- HDF5
- Annotation Types
- language_instructionsgrasp_descriptionsobject_descriptionssegmentationgrasp_poses
- License
- MIT
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