CLARU
ethHuiZhangcc-by-nc-4.0

GraspXL

A large-scale dataset of 10M+ physically plausible dexterous grasping motion sequences over 500k+ Objaverse objects, generated with physics simulation for multiple hand models including Allegro, SharpA, MANO, and LEAP hands.

Downloads6
Episodes10M+

Why This Matters for Physical AI

GraspXL provides a massive, physically-simulated benchmark for training dexterous manipulation models and enables zero-shot generalization to novel objects through diverse hand-object interaction data.

Technical Profile

Modalities
proprioception3d
Robot Embodiments
Allegro HandSharpA HandMANO HandLEAP Handdexterous_hand
Action Space
joint_positions
Environment
simulationtabletop
Task Types
graspingdexterous_manipulationmotion_generation
Episodes
10M+
Data Format
npy
Annotation Types
hand_poseobject_posewrist_positionwrist_orientation
License
cc-by-nc-4.0
Part of the GraspXL family

Access

View on HuggingFace

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