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Datasets:
SteveNguyen
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sim_grabette_grasp_eval

Tasks:
Robotics
Modalities:
Tabular
Time-series
Video
Formats:
parquet
Size:
10K - 100K
Tags:
LeRobot
sim
grabette
grasp
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
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float32
0
6.58
frame_index
int64
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329
episode_index
int64
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39
index
int64
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12.6k
task_index
int64
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1.44
72
0
72
0
[ 0.4206979274749756, -0.05290689319372177, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.076014558396576e-16, 3.733450210292897e-22 ]
1.46
73
0
73
0
[ 0.42539483308792114, -0.04902001842856407, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.178825829347527e-16, 3.90692261661717e-22 ]
1.48
74
0
74
0
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1.5
75
0
75
0
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1.52
76
0
76
0
[ 0.4378204047679901, -0.03873731568455696, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.492379956366532e-16, 3.6987557290280423e-22 ]
1.54
77
0
77
0
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1.56
78
0
78
0
[ 0.4443002939224243, -0.03337492048740387, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.705702557154567e-16, 1.0272815551584515e-22 ]
1.58
79
0
79
0
[ 0.44687420129776, -0.03124489262700081, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.813655847490944e-16, 5.329395843605229e-22 ]
1.6
80
0
80
0
[ 0.44894859194755554, -0.029528237879276276, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -6.922486346323321e-16, 5.953896001501633e-22 ]
1.62
81
0
81
0
[ 0.4504818618297577, -0.028259405866265297, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.032119408873221e-16, 6.647785626798725e-22 ]
1.64
82
0
82
0
[ 0.45143234729766846, -0.02747284434735775, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.142576740359918e-16, 3.8375336540874607e-22 ]
1.66
83
0
83
0
[ 0.45175841450691223, -0.02720300294458866, 0.6396945118904114, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.25388904572775e-16, -3.5523883309716735e-22 ]
1.68
84
0
84
0
[ 0.4517665505409241, -0.027205444872379303, 0.6395764350891113, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.363588282726654e-16, -7.195307601603959e-22 ]
1.7
85
0
85
0
[ 0.4517905116081238, -0.02721264213323593, 0.6392285227775574, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.468458902530617e-16, -9.485142355342404e-22 ]
1.72
86
0
86
0
[ 0.4518296420574188, -0.02722439542412758, 0.6386604309082031, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.568625313103766e-16, -1.253825569690765e-21 ]
1.74
87
0
87
0
[ 0.4518832862377167, -0.027240505442023277, 0.6378816366195679, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.665790050670083e-16, -9.623920280401822e-22 ]
1.76
88
0
88
0
[ 0.4519507586956024, -0.02726077474653721, 0.6369017362594604, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.761504773709819e-16, -1.2260699846788814e-21 ]
1.78
89
0
89
0
[ 0.4520314633846283, -0.027285005897283554, 0.6357303857803345, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.856723982475411e-16, -1.5487285847113823e-21 ]
1.8
90
0
90
0
[ 0.4521246552467346, -0.027313001453876495, 0.6343770623207092, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -7.951973896185341e-16, -1.357908962998231e-21 ]
1.82
91
0
91
0
[ 0.45222973823547363, -0.027344562113285065, 0.6328514218330383, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.047427097802613e-16, -1.3232145322204743e-21 ]
1.84
92
0
92
0
[ 0.4523460268974304, -0.027379490435123444, 0.6311629414558411, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.143142350237941e-16, -1.0179031980639496e-21 ]
1.86
93
0
93
0
[ 0.45247289538383484, -0.027417587116360664, 0.6293213367462158, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.239088948546987e-16, -4.697305960276386e-22 ]
1.88
94
0
94
0
[ 0.4526096284389496, -0.02745865471661091, 0.6273360252380371, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.335312420750668e-16, -1.3666368948100472e-22 ]
1.9
95
0
95
0
[ 0.4527556002140045, -0.027502495795488358, 0.6252167224884033, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.431725416576297e-16, -8.236142039549597e-22 ]
1.92
96
0
96
0
[ 0.4529101550579071, -0.027548912912607193, 0.6229729056358337, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.52837399344038e-16, -1.389134021380149e-21 ]
1.94
97
0
97
0
[ 0.45307260751724243, -0.027597704902291298, 0.620614230632782, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.625236975519238e-16, -1.7742426372022903e-21 ]
1.96
98
0
98
0
[ 0.45324233174324036, -0.027648678049445152, 0.6181501746177673, -2.4260947704315186, 1.2491718530654907, -0.33787626028060913, -8.72229371638478e-16, -2.1662900987903046e-21 ]
1.98
99
0
99
0
End of preview. Expand in Data Studio

This dataset was created using LeRobot.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v3.0",
    "robot_type": "openarm_gripette_sim",
    "total_episodes": 40,
    "total_frames": 12615,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 200,
    "fps": 50,
    "splits": {
        "train": "0:40"
    },
    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
    "features": {
        "observation.images.cam0": {
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            "names": [
                "channels",
                "height",
                "width"
            ],
            "info": {
                "video.height": 972,
                "video.width": 1296,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 50,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "action": {
            "dtype": "float32",
            "shape": [
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            "names": [
                "x",
                "y",
                "z",
                "ax",
                "ay",
                "az",
                "proximal",
                "distal"
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        "timestamp": {
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        "frame_index": {
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        "episode_index": {
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        "index": {
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        "task_index": {
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        }
    }
}

Citation

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