Datasets:

shadowHokage
/

pick_cube_omx_f

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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Pick-the-cube re-recording (OpenMANIPULATOR OMX-F)

Everything is in pick_cube_omx_f_FULL.zip (498 MB, sha256 a15ea757b54f12377a4314bad45c3a9301f7ecb03126783b06c731bb546652ae):

Path in the zip	Content
`lerobot/Task_1_pick_the_cube_MCAP_lerobot_v30_augmented/`	LeRobot v3.0 dataset: 34 episodes, 11,394 frames at 15 fps, `camera1` + `camera2` video, plus `observation.asset_joint_pos` (cube pose), `observation.asset_valid`, `observation.effort`
`rosbag2/Task_1_pick_the_cube_MCAP/<n>/`	Raw MCAP per episode (joint states with effort, leader actions, `/cube_pose`, `/tf`), camera videos and camera_info
`outcomes.jsonl`	One line per episode and probe: `episode_index`, `outcome` (PASS / FAIL / N/A), `reason`, `task`, `category`, lift / hold / slide metrics
`README.md`	The document below

Episodes: 20 field picks (12 PASS, 8 FAIL), probe:free_sweep x2, probe:push_ramp x3, probe:repeat x5, probe:grip_ladder x3 (gentle / normal / firm), probe:known_load x1.

nwaves pick-the-cube re-recording (OpenMANIPULATOR OMX-F)

Generated 2026-09-19T17:26:15 by the recording assistant from the live session.

Robot

Arm: ROBOTIS OMX-F follower (5 arm joints + gripper), teleoperated with an OMX-L leader. NOTE: the spec was written for the OMY 6-DoF; this rig is the OMX-F.
Servos (follower): joint1-3 XL430-W250 (IDs 11-13); joint4, joint5, gripper XL330-M288 (IDs 14-16).
Control / recording rate: 15 Hz LeRobot v3.0 export (Cyclo Intelligence), /joint_states at 100 Hz, cameras at 30 Hz.

Cameras

Policy cameras: camera1 = Logitech C270 (left), camera2 = Sonix USB2.0 CAM1 (wrist).
Tag camera (independent, NOT consumed by the policy): Logitech Brio 100, 1280x720 MJPEG, fixed exposure, mounted ~55 cm from the workspace.

Cube pose (`observation.asset_joint_pos`)

AprilTag tag36h11 ID 0, black square 24 mm, on the top face of a 30 mm cube.
Value: cube center [x, y, z, qx, qy, qz, qw] in the robot base frame link0 (meters), NaN when the tag was not seen within 0.1 s (observation.asset_valid = 0).
Tag-camera intrinsics (1280x720, plumb_bob): K = [1294.82, 0, 634.639, 0, 1290.03, 322.024, 0, 0, 1], D = [0.1223, -0.4727, 0, 0, 0], RMS 0.213 px. Calibrated with a single ArUco 4x4 marker (40 views, k1/k2 only) instead of a checkerboard.
Extrinsics link0 -> tag_cam_optical_frame: t = [-0.0351, -0.2310, 0.5144] m, q(xyzw) = [-0.7808, 0.5632, -0.0875, 0.2558]. Touch-point calibration with the cube tag (9 points, mean residual 8.1 mm, mostly vertical), then z corrected by -14.5 mm so a cube resting on the table reads center z = 15 mm.
Measured noise with a static cube: ~1 mm std at 30 Hz.

Effort (`observation.effort`)

Raw Dynamixel readings, one value per joint [joint1..joint5, gripper_joint_1]:
- joint1-3 (XL430, no current sensor): Present_Load, 0.1 % of max torque per LSB, signed. Raw MCAP values arrive unsigned-wrapped (65518 = -18); the dataset has them corrected.
- joint4, joint5, gripper (XL330): Present_Current, 1 mA per LSB, signed.

Outcomes (`outcomes.jsonl`)

Success definition: **PASS if, at any time during the episode, the cube center is

= 5.0 cm above its start height (median of the first 1 s) and stays there continuously for >= 2 s**, measured by the tag camera. This allows the operator to place the cube back before stopping, while a slip or drop (lifted but not held) is a FAIL. held_s in outcomes.jsonl is the longest such hold. push_ramp: PASS if the cube slid >= 1 cm. free_sweep: N/A (no cube). Proposed automatically, confirmed or overridden by the operator.
episode_index is Cyclo's episode number at recording time; check it against the exported dataset if episodes were discarded.

Batch

Field picks: 12 PASS, 8 FAIL.
probe:free_sweep x2, probe:push_ramp x3, probe:repeat x5, probe:grip_ladder x3 (levels: firm, gentle, normal), probe:known_load x1 (2 taped 3 cm cubes, mass not measured).
Cube start pose: taped outline at x=23.2, y=-17.6 cm in link0.

Files

LeRobot v3.0 dataset (Cyclo export + augment_lerobot.py for the cube pose / effort columns), raw MCAP per episode, outcomes.jsonl, this README.
Time base: one host clock for arm, policy cameras and tag camera (poses stamped with the camera frame capture time).

Notes

Probes were marked in the recording assistant; Cyclo recorded every episode under the task text "pick the cube". The LeRobot dataset has the correct per-episode task (probe:* via augment_lerobot.py --outcomes); the raw MCAP / episode_info.json still show "pick the cube". outcomes.jsonl (category) is the authoritative label.
Episodes 10 and 17 (free sweep) have no cube pose by design (cube removed).
Known-load mass was not measured (2 taped 3 cm cubes).

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Total file size:

522 MB