RobotPosterior Dataset

Robotic grasp posterior data collected from Isaac Sim physical validation across multiple rounds.

84 objects (OakInk + DexYCB)
1861 successful grasps verified by physics simulation (Franka Panda in Isaac Sim)
Per-object HDF5 files with full grasp pose data

HDF5 Schema

Each {obj_id}_robot_gt.hdf5 contains:

/
├── attrs:
│   ├── obj_id          (str)
│   ├── n_successful    (int)
│   └── sources         (str)  e.g. "R1(×5) | R2(×13) | NEW(×20)"
│
└── successful_grasps/
    ├── attrs: count
    └── grasp_N/
        ├── grasp_point         (3,)   float32  — contact midpoint, canonical mesh frame
        ├── rotation            (3,3)  float32  — gripper rotation matrix
        ├── approach_dir        (3,)   float32  — rotation[:, 2]
        ├── finger_dir          (3,)   float32  — rotation[:, 0]
        ├── [contact_points_local] (2,3) float32 — actual finger tip positions
        └── attrs:
            ├── gripper_width   (float)  meters
            ├── score           (float)
            └── approach_type   (str)

Coordinate Frame

grasp_point, rotation: canonical mesh local frame (Z-up, object bottom at Z=0)
contact_points_local: world offset from OBJECT_POSITION in Isaac Sim

Data Sources

Label	Round	Server	Objects	Grasps
R1	Round 1	Titan	48	~231
R2	Round 2	Titan	55	~592
R3	Round 3	Titan	43	~181
D1	DexYCB R1	Titan	7	~14
D2	DexYCB R2	Titan	6	~41
NEW	Round 0+1	RTX5090	70	~802

Candidate Generation

Grasp candidates generated with 50% Human-Prior guided + 50% random sampling (v5.1 Raycast scorer).
All entries physically verified in Isaac Sim with Franka Panda robot.

Usage

import h5py, numpy as np

with h5py.File('C28001_robot_gt.hdf5', 'r') as f:
    print(f"n_successful: {f.attrs['n_successful']}")
    for key in f['successful_grasps'].keys():
        g = f['successful_grasps'][key]
        grasp_point  = g['grasp_point'][:]    # (3,) meters, mesh local frame
        approach_dir = g['approach_dir'][:]   # (3,) unit vector
        width        = g.attrs['gripper_width']

Datasets:

UCBProject
/

RobotPosterior