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Datasets:
ninetyone
/
so100_training

Tasks:
Robotics
Modalities:
Tabular
Time-series
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< 1K
Tags:
LeRobot
so100
tutorial
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pandas
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sequence
observation.state
sequence
timestamp
float32
0
29.8
frame_index
int64
0
894
episode_index
int64
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0
index
int64
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[ -4.658203125, 64.6875, 108.193359375, 84.0234375, 9.052734375, 1.7454545497894287 ]
2.433333
73
0
73
0
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[ -4.658203125, 62.666015625, 108.720703125, 83.671875, 8.701171875, 0 ]
2.466667
74
0
74
0
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[ -5.009765625, 60.556640625, 109.599609375, 83.232421875, 8.26171875, -1.0909091234207153 ]
2.5
75
0
75
0
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[ -5.2734375, 58.359375, 109.775390625, 83.232421875, 7.822265625, -1.8181817531585693 ]
2.533333
76
0
76
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2.566667
77
0
77
0
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[ -5.185546875, 54.84375, 109.248046875, 83.232421875, 7.294921875, -2.545454502105713 ]
2.6
78
0
78
0
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2.633333
79
0
79
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2.666667
80
0
80
0
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[ -4.921875, 51.50390625, 108.544921875, 83.49609375, 7.119140625, -2.909090995788574 ]
2.7
81
0
81
0
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[ -4.921875, 50.537109375, 109.51171875, 83.49609375, 7.119140625, -2.909090995788574 ]
2.733333
82
0
82
0
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[ -4.921875, 49.306640625, 111.181640625, 83.49609375, 7.20703125, -2.909090995788574 ]
2.766667
83
0
83
0
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[ -4.833984375, 48.1640625, 112.587890625, 83.49609375, 7.55859375, -2.909090995788574 ]
2.8
84
0
84
0
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[ -4.921875, 47.28515625, 115.576171875, 83.49609375, 7.646484375, -2.909090995788574 ]
2.833333
85
0
85
0
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[ -4.921875, 47.28515625, 117.59765625, 83.056640625, 7.55859375, -2.909090995788574 ]
2.866667
86
0
86
0
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[ -4.921875, 47.4609375, 118.4765625, 82.177734375, 8.0859375, -2.981818199157715 ]
2.9
87
0
87
0
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[ -4.833984375, 47.900390625, 119.00390625, 81.5625, 8.26171875, -2.981818199157715 ]
2.933333
88
0
88
0
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2.966667
89
0
89
0
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[ -4.74609375, 49.306640625, 120.41015625, 80.244140625, 8.26171875, -2.981818199157715 ]
3
90
0
90
0
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[ -4.74609375, 50.185546875, 121.11328125, 79.453125, 8.26171875, -2.981818199157715 ]
3.033333
91
0
91
0
[ -6.50390625, -168.134765625, 154.3359375, 63.45703125, 8.0859375, -3.7001895904541016 ]
[ -4.833984375, 51.240234375, 121.9921875, 78.662109375, 8.26171875, -2.981818199157715 ]
3.066667
92
0
92
0
[ -6.416015625, -168.134765625, 157.939453125, 61.787109375, 7.470703125, -3.7001895904541016 ]
[ -5.09765625, 52.3828125, 122.958984375, 77.6953125, 7.998046875, -2.981818199157715 ]
3.1
93
0
93
0
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[ -5.09765625, 53.61328125, 123.92578125, 76.640625, 7.734375, -2.981818199157715 ]
3.133333
94
0
94
0
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[ -5.09765625, 54.66796875, 124.98046875, 75.76171875, 7.20703125, -2.981818199157715 ]
3.166667
95
0
95
0
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[ -5.09765625, 55.8984375, 125.771484375, 75.05859375, 6.6796875, -2.981818199157715 ]
3.2
96
0
96
0
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[ -5.09765625, 57.12890625, 126.73828125, 74.35546875, 6.328125, -2.981818199157715 ]
3.233333
97
0
97
0
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[ -5.185546875, 58.359375, 127.705078125, 73.4765625, 6.240234375, -2.981818199157715 ]
3.266667
98
0
98
0
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[ -5.185546875, 59.58984375, 128.671875, 72.861328125, 6.240234375, -2.981818199157715 ]
3.3
99
0
99
0
End of preview. Expand in Dataset Viewer.

This dataset was created using LeRobot.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v2.0",
    "robot_type": "so100",
    "total_episodes": 1,
    "total_frames": 895,
    "total_tasks": 1,
    "total_videos": 1,
    "total_chunks": 1,
    "chunks_size": 1000,
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    "splits": {
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    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
    "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
    "features": {
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                "main_shoulder_lift",
                "main_elbow_flex",
                "main_wrist_flex",
                "main_wrist_roll",
                "main_gripper"
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                "main_shoulder_lift",
                "main_elbow_flex",
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                "main_wrist_roll",
                "main_gripper"
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        "observation.images.phone": {
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                "channels"
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        "timestamp": {
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        "frame_index": {
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            "names": null
        }
    }
}

Citation

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