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list | observation.state
list | timestamp
float64 | task_index
int64 | episode_index
int64 | frame_index
int64 | index
int64 |
|---|---|---|---|---|---|---|
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0.10280181088669897,
-0.24396250643261397,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10280180722475052,
-0.23168766498565674,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.133333 | 0 | 0 | 94 | 94 |
[
0.1043361662730676,
-0.25009992797808855,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10280180722475052,
-0.24396251142024994,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.166667 | 0 | 0 | 95 | 95 |
[
0.1043361662730676,
-0.2562373495235631,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10433616489171982,
-0.25009992718696594,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.2 | 0 | 0 | 96 | 96 |
[
0.10587052165943625,
-0.25777170490993173,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10433616489171982,
-0.25623735785484314,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.233333 | 0 | 0 | 97 | 97 |
[
0.10587052165943625,
-0.260840415682669,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10587052255868912,
-0.25777170062065125,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.266667 | 0 | 0 | 98 | 98 |
[
0.10587052165943625,
-0.26237477106903767,
0.37284835888757983,
0.01074048770458049,
0.006137421545474565,
2.1619067393934155
] |
[
0.10587052255868912,
-0.26084041595458984,
0.37284836173057556,
0.010740487836301327,
0.006137421354651451,
2.1619067192077637
] | 3.3 | 0 | 0 | 99 | 99 |
End of preview. Expand
in Data Studio
example_dataset
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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