Towards Human-level Dexterous Teleoperation
Paper • 2607.11481 • Published
Datasets:
ArXiv:
License:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
input_dir: string
output_path: string
source_episode_count: int64
output_episode_count: int64
source_frame_count: int64
output_frame_count: int64
dropped_short_segment_frames: int64
split_gap_seconds: double
min_segment_frames: int64
front_image_shape: list<item: int64>
child 0, item: int64
wrist_image_shape: null
wrist_camera_rotated_180: bool
instructions: list<item: string>
child 0, item: string
source_format: string
excluded_incomplete_sources: list<item: null>
child 0, item: null
hand_joint_order: string
hand_joint_names: list<item: string>
child 0, item: string
hand_joint_faas_idx: list<item: int64>
child 0, item: int64
tactile_channel_names: list<item: string>
child 0, item: string
tactile_function_area_idx: list<item: int64>
child 0, item: int64
tactile_f6_order: list<item: string>
child 0, item: string
episodes: list<item: struct<source_episode: int64, path: string, source_format: string, instructions: list<ite (... 225 chars omitted)
child 0, item: struct<source_episode: int64, path: string, source_format: string, instructions: list<item: null>, s (... 213 chars omitted)
child 0, source_episode: int64
child 1, path: string
child 2, source_format: string
child 3, instructions: list<item: null>
child 0, item: null
child 4, source_frames: int64
child 5, segments: list<item: struct<source_episode: int64, source_start: int64, source_end: int64, gap_before_seconds: (... 22 chars omitted)
child 0, item: struct<source_episode: int64, source_start: int64, source_end: int64, gap_before_seconds: null, leng (... 10 chars omitted)
child 0, source_episode: int64
child 1, source_start: int64
child 2, source_end: int64
child 3, gap_before_seconds: null
child 4, length: int64
child 6, dropped_ranges: list<item: null>
child 0, item: null
child 7, max_gap_seconds: double
hand_joint_order_correction: struct<updated_at: string, previous_order: string, corrected_order: string, reason: string, joint_va (... 21 chars omitted)
child 0, updated_at: string
child 1, previous_order: string
child 2, corrected_order: string
child 3, reason: string
child 4, joint_values_reordered: bool
release: struct<name: string, version: string, source_batch: string>
child 0, name: string
child 1, version: string
child 2, source_batch: string
wrist_camera_published: bool
publication_revision: string
source_inventory_sha256: string
archive_bytes: int64
files: int64
source_summary_sha256: string
sha256: string
file: string
uncompressed_bytes: int64
archive_mtime_ns: int64
to
{'file': Value('string'), 'files': Value('int64'), 'uncompressed_bytes': Value('int64'), 'archive_bytes': Value('int64'), 'sha256': Value('string'), 'source_summary_sha256': Value('string'), 'source_inventory_sha256': Value('string'), 'archive_mtime_ns': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
input_dir: string
output_path: string
source_episode_count: int64
output_episode_count: int64
source_frame_count: int64
output_frame_count: int64
dropped_short_segment_frames: int64
split_gap_seconds: double
min_segment_frames: int64
front_image_shape: list<item: int64>
child 0, item: int64
wrist_image_shape: null
wrist_camera_rotated_180: bool
instructions: list<item: string>
child 0, item: string
source_format: string
excluded_incomplete_sources: list<item: null>
child 0, item: null
hand_joint_order: string
hand_joint_names: list<item: string>
child 0, item: string
hand_joint_faas_idx: list<item: int64>
child 0, item: int64
tactile_channel_names: list<item: string>
child 0, item: string
tactile_function_area_idx: list<item: int64>
child 0, item: int64
tactile_f6_order: list<item: string>
child 0, item: string
episodes: list<item: struct<source_episode: int64, path: string, source_format: string, instructions: list<ite (... 225 chars omitted)
child 0, item: struct<source_episode: int64, path: string, source_format: string, instructions: list<item: null>, s (... 213 chars omitted)
child 0, source_episode: int64
child 1, path: string
child 2, source_format: string
child 3, instructions: list<item: null>
child 0, item: null
child 4, source_frames: int64
child 5, segments: list<item: struct<source_episode: int64, source_start: int64, source_end: int64, gap_before_seconds: (... 22 chars omitted)
child 0, item: struct<source_episode: int64, source_start: int64, source_end: int64, gap_before_seconds: null, leng (... 10 chars omitted)
child 0, source_episode: int64
child 1, source_start: int64
child 2, source_end: int64
child 3, gap_before_seconds: null
child 4, length: int64
child 6, dropped_ranges: list<item: null>
child 0, item: null
child 7, max_gap_seconds: double
hand_joint_order_correction: struct<updated_at: string, previous_order: string, corrected_order: string, reason: string, joint_va (... 21 chars omitted)
child 0, updated_at: string
child 1, previous_order: string
child 2, corrected_order: string
child 3, reason: string
child 4, joint_values_reordered: bool
release: struct<name: string, version: string, source_batch: string>
child 0, name: string
child 1, version: string
child 2, source_batch: string
wrist_camera_published: bool
publication_revision: string
source_inventory_sha256: string
archive_bytes: int64
files: int64
source_summary_sha256: string
sha256: string
file: string
uncompressed_bytes: int64
archive_mtime_ns: int64
to
{'file': Value('string'), 'files': Value('int64'), 'uncompressed_bytes': Value('int64'), 'archive_bytes': Value('int64'), 'sha256': Value('string'), 'source_summary_sha256': Value('string'), 'source_inventory_sha256': Value('string'), 'archive_mtime_ns': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
TeleDexter_Bulb
Real-world Franka + Sharpa Wave demonstrations collected using TeleDexter.
Contact: wangty153@gmail.com
Versions
Each version contains its own source batch; 1.0.1 does not include the 1.0.0 trajectories.
- 1.0.0: bulb_tac_80; 80 trajectories, 44,142 frames. Published RGB streams: camera_main_rgb.
- 1.0.1: realworld_bulb_sft_260909; 75 trajectories, 48,894 frames. Published RGB streams: camera_main_rgb, right_wrist_camera_rgb.
Each version contains its own metadata.json and OXT metadata/schema reports. RGB and tactile payloads retain their source values and real sampling intervals. The metadata/schema checks have no errors; timestamp-gap warnings are retained. Codex direct multimodal review is complete with documented warnings; no external VLM API was called. Organizer acceptance is not assumed.
Data collection contributors
- 李浦豪 — TeleDexter / BIGAI
- 陈泽源 — TeleDexter / 北京通研院
- 王天宇 — TeleDexter / 北京通研院
- 黄奥申 — TeleDexter / 北京通研院
- 冯元莅 — TeleDexter / 北京通研院
- 黄思远 — BIGAI
Reference
TeleDexter: Towards Human-level Dexterous Teleoperation. Paper · Project blog
The reference.authors field lists the paper authors; collection contributors are listed above. Data format: Open-X-Tactile.
Reading the archive
Unzip each version's *.zarr.zip to recover its Zarr v2 directory. Archive compression is ZIP_STORED because the Zarr chunks are already compressed. Use the per-version metadata.json for the corresponding trajectory/frame counts.
Release notes
OXT organizer guidance relayed by the contributor on 2026-10-25: label is [] because these datasets are neither umi nor ego and contain no supplementary joints or tactile data. code_trigger is FTP_1_Source. The dataset license is specified in the card metadata above. Third-party illustration and logo sources are documented in ASSET_SOURCES.json.
OXT repository layout
Data and review materials are under TeleDexter_Bulb/1.0.0/ and TeleDexter_Bulb/1.0.1/.
Use TeleDexter_Bulb/SHA256SUMS from within TeleDexter_Bulb/ to check the two archives.
Asset provenance: TeleDexter_Bulb/ASSET_SOURCES.json. Codex direct multimodal review is complete with documented warnings; no external VLM API was called. Organizer acceptance of the review method and dataset is not assumed.
Multimodal review
Codex direct multimodal review is complete with documented warnings; no external VLM API was called. Organizer acceptance of the review method and dataset is not assumed.
Per-version oxt_check_output/ contains vlm_review.json, vlm_review_result.json, warning_review.json and inspected evidence PNGs. Scores are ordinal Codex judgments, not measured probabilities.
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