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Datasets:
VGalaxies666
/
long_cable_insertion

Tasks:
Robotics
Modalities:
Time-series
Size:
10K<n<100K
Tags:
tsfile
timeseries
time-series
lerobot
robotics
real
License:
Dataset card Data Studio Files
xet
 Community
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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
episode_index: int64
stats: struct<observation.images.video_left: struct<min: list<item: list<item: list<item: double>>>, max: l (... 2495 chars omitted)
  child 0, observation.images.video_left: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
      child 0, min: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item: double>>
              child 0, item: list<item: double>
                  child 0, item: double
      child 1, max: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item: double>>
              child 0, item: list<item: double>
                  child 0, item: double
      child 2, mean: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item: double>>
              child 0, item: list<item: double>
                  child 0, item: double
      child 3, std: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item: double>>
              child 0, item: list<item: double>
                  child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 1, observation.images.video_overhead: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
      child 0, min: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item
...
: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 13, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 14, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
length: int64
tasks: list<item: string>
  child 0, item: string
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              episode_index: int64
              stats: struct<observation.images.video_left: struct<min: list<item: list<item: list<item: double>>>, max: l (... 2495 chars omitted)
                child 0, observation.images.video_left: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
                    child 0, min: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item: double>>
                            child 0, item: list<item: double>
                                child 0, item: double
                    child 1, max: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item: double>>
                            child 0, item: list<item: double>
                                child 0, item: double
                    child 2, mean: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item: double>>
                            child 0, item: list<item: double>
                                child 0, item: double
                    child 3, std: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item: double>>
                            child 0, item: list<item: double>
                                child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 1, observation.images.video_overhead: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
                    child 0, min: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item
              ...
              : list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 13, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 14, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
              length: int64
              tasks: list<item: string>
                child 0, item: string
              to
              {'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

episode_index
int64
tasks
list
length
int64
0
[ "insert the cable into the holders" ]
579
1
[ "insert the cable into the holders" ]
567
2
[ "insert the cable into the holders" ]
558
3
[ "insert the cable into the holders" ]
490
4
[ "insert the cable into the holders" ]
540
5
[ "insert the cable into the holders" ]
507
6
[ "insert the cable into the holders" ]
436
7
[ "insert the cable into the holders" ]
521
8
[ "insert the cable into the holders" ]
524
9
[ "insert the cable into the holders" ]
461
10
[ "insert the cable into the holders" ]
472
11
[ "insert the cable into the holders" ]
450
12
[ "insert the cable into the holders" ]
549
13
[ "insert the cable into the holders" ]
444
14
[ "insert the cable into the holders" ]
414
15
[ "insert the cable into the holders" ]
465
16
[ "insert the cable into the holders" ]
436
17
[ "insert the cable into the holders" ]
437
18
[ "insert the cable into the holders" ]
413
19
[ "insert the cable into the holders" ]
420
20
[ "insert the cable into the holders" ]
463
21
[ "insert the cable into the holders" ]
423
22
[ "insert the cable into the holders" ]
403
23
[ "insert the cable into the holders" ]
420
24
[ "insert the cable into the holders" ]
409
25
[ "insert the cable into the holders" ]
413
26
[ "insert the cable into the holders" ]
418
27
[ "insert the cable into the holders" ]
390
28
[ "insert the cable into the holders" ]
409
29
[ "insert the cable into the holders" ]
406
30
[ "insert the cable into the holders" ]
393
31
[ "insert the cable into the holders" ]
448
32
[ "insert the cable into the holders" ]
405
33
[ "insert the cable into the holders" ]
395
34
[ "insert the cable into the holders" ]
426
35
[ "insert the cable into the holders" ]
408
36
[ "insert the cable into the holders" ]
349
37
[ "insert the cable into the holders" ]
393
38
[ "insert the cable into the holders" ]
378
39
[ "insert the cable into the holders" ]
413
40
[ "insert the cable into the holders" ]
395
41
[ "insert the cable into the holders" ]
409
42
[ "insert the cable into the holders" ]
357
43
[ "insert the cable into the holders" ]
430
44
[ "insert the cable into the holders" ]
382
45
[ "insert the cable into the holders" ]
400
46
[ "insert the cable into the holders" ]
402
47
[ "insert the cable into the holders" ]
373
48
[ "insert the cable into the holders" ]
362
49
[ "insert the cable into the holders" ]
507
50
[ "insert the cable into the holders" ]
470
51
[ "insert the cable into the holders" ]
408
52
[ "insert the cable into the holders" ]
419
53
[ "insert the cable into the holders" ]
425
54
[ "insert the cable into the holders" ]
439
55
[ "insert the cable into the holders" ]
421
56
[ "insert the cable into the holders" ]
441
57
[ "insert the cable into the holders" ]
402
58
[ "insert the cable into the holders" ]
384
59
[ "insert the cable into the holders" ]
440
60
[ "insert the cable into the holders" ]
407
61
[ "insert the cable into the holders" ]
415
62
[ "insert the cable into the holders" ]
405
63
[ "insert the cable into the holders" ]
395
64
[ "insert the cable into the holders" ]
430
65
[ "insert the cable into the holders" ]
405
66
[ "insert the cable into the holders" ]
419
67
[ "insert the cable into the holders" ]
418
68
[ "insert the cable into the holders" ]
422
69
[ "insert the cable into the holders" ]
478
70
[ "insert the cable into the holders" ]
486
71
[ "insert the cable into the holders" ]
459
72
[ "insert the cable into the holders" ]
407
73
[ "insert the cable into the holders" ]
417
74
[ "insert the cable into the holders" ]
414
75
[ "insert the cable into the holders" ]
450
76
[ "insert the cable into the holders" ]
447
77
[ "insert the cable into the holders" ]
448
78
[ "insert the cable into the holders" ]
443
79
[ "insert the cable into the holders" ]
446
80
[ "insert the cable into the holders" ]
435
81
[ "insert the cable into the holders" ]
453
82
[ "insert the cable into the holders" ]
519
83
[ "insert the cable into the holders" ]
448
84
[ "insert the cable into the holders" ]
455
85
[ "insert the cable into the holders" ]
453
86
[ "insert the cable into the holders" ]
444
87
[ "insert the cable into the holders" ]
438
88
[ "insert the cable into the holders" ]
415
89
[ "insert the cable into the holders" ]
411
90
[ "insert the cable into the holders" ]
406
91
[ "insert the cable into the holders" ]
419
92
[ "insert the cable into the holders" ]
442
93
[ "insert the cable into the holders" ]
433
94
[ "insert the cable into the holders" ]
470
95
[ "insert the cable into the holders" ]
605
96
[ "insert the cable into the holders" ]
600
97
[ "insert the cable into the holders" ]
453
98
[ "insert the cable into the holders" ]
446
99
[ "insert the cable into the holders" ]
432
End of preview.

Long Cable Insertion (TsFile)

Apache TsFile version of DistantSky/long_cable_insertion.

Overview

A real-robot LeRobot (v2.1) teleoperation dataset of a long-cable insertion task on a 14-DoF dual-arm "hessian" robot, recorded at 60 fps. Every episode is a trajectory for the single task "insert the cable into the holders", with synchronized joint state, joint velocity, and action commands, plus per-frame subgoal metadata.

  • Robot: hessian, dual-arm, 14 joints.
  • Episodes: 114 (episode_index 0–113).
  • Frames: 50,219 time-series rows.
  • Task: 1 — insert the cable into the holders.
  • Sampling rate: 60 fps (from meta/info.json).

Schema (TsFile structure)

All 114 episodes are stored in a single TsFile table. episode_index, task_index and prompt are TAG columns (the TsFile device dimension); prompt is constant within an episode, so it is stored once as a TAG rather than repeated per frame. Select one episode with WHERE episode_index=0.

  • Time (INT64, milliseconds) — round(timestamp * 1000); restarts at 0 for each episode, stepping by ~17 ms (60 fps).
  • episode_index (TAG) — source episode id, 0–113.
  • task_index (TAG) — source task id (0).
  • prompt (TAG, STRING) — the task instruction text.
  • frame_index (FIELD, INT64) — frame number within the episode.
  • sample_index (FIELD, INT64) — the source global index column, renamed.
  • observation_state_0 … _13 (FIELD, FLOAT) — joint state, flattened from the 14-element observation.state vector.
  • observation_velocity_0 … _13 (FIELD, FLOAT) — joint velocity, flattened from observation.velocity.
  • action_0 … _13 (FIELD, FLOAT) — joint action command, flattened from action.
  • source_action_time_s (FIELD, FLOAT) — source source.action_time_s.
  • metadata_failure, metadata_subgoal_switch (FIELD, BOOLEAN) — per-frame metadata flags.
  • metadata_subgoal_order_0 … _2 (FIELD, FLOAT) — the source metadata.subgoal_order int64[3] indices, stored as FLOAT like the other flattened vectors.
  • metadata_subgoal_order_string (FIELD, STRING) — string form of the subgoal order.

The source timestamp column is dropped because it equals Time / 1000 seconds. No other columns or rows are dropped.

Videos & raw dumps

  • The three camera video streams (observation.images.video_left, observation.images.video_overhead, observation.images.video_right) are NOT included in this repository. Obtain them from the original dataset: https://huggingface.co/datasets/DistantSky/long_cable_insertion (the videos/ directory).
  • The original dataset also ships raw_episodes/*.npz (raw NumPy dumps that duplicate the per-episode Parquet frame data). These are NOT included here; the Parquet frame data is the canonical time series.

Usage

Read the .tsfile file with the Apache TsFile Java or Python SDK.

Source & license

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