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sequence | observation.state
sequence | timestamp
float64 | task_index
int64 | episode_index
int64 | frame_index
int64 | index
int64 |
|---|---|---|---|---|---|---|
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] | 3.133333 | 0 | 0 | 94 | 94 |
[
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0.8745825702301255,
0.201000555614292,
-0.032221463113741466,
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0.871513843536377,
0.19946619868278503,
-0.032221462577581406,
0.009206132031977177
] | 3.166667 | 0 | 0 | 95 | 95 |
[
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-0.17491651404602512,
0.889926124093812,
0.201000555614292,
-0.032221463113741466,
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-0.17338216304779053,
0.8745825886726379,
0.20100055634975433,
-0.032221462577581406,
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] | 3.2 | 0 | 0 | 96 | 96 |
[
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0.9037353225711298,
0.19946620022792338,
-0.032221463113741466,
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-0.17491652071475983,
0.8899261355400085,
0.20100055634975433,
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] | 3.233333 | 0 | 0 | 97 | 97 |
[
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0.19946620022792338,
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0.903735339641571,
0.19946619868278503,
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0.009206132031977177
] | 3.266667 | 0 | 0 | 98 | 98 |
[
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0.9129414548893416,
0.19946620022792338,
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0.9129414558410645,
0.19946619868278503,
-0.024549685418605804,
0.007671777158975601
] | 3.3 | 0 | 0 | 99 | 99 |
End of preview. Expand
in Data Studio
data1
This dataset was generated using a phospho starter pack.
This dataset contains a series of episodes recorded with a robot and multiple cameras. It can be directly used to train a policy using imitation learning. It's compatible with LeRobot and RLDS.
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