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
Part of the PRISM family

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