The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
id: string
name: string
startTime: int64
endTime: int64
sampleRate: int64
devices: list<item: struct<id: string, position: string, connectionId: string>>
snapshots: list<item: struct<time: int64, deviceData: struct<E4:B3:23:AD:5A:B2: list<item: double>, E4:B3:23:AD:24:0E: list<item: double>, E4:B3:23:AD:22:26: list<item: double>, right_hand_virtual: list<item: double>, right_forearm_virtual: list<item: double>, left_hand_virtual: list<item: double>, left_forearm_virtual: list<item: double>>>>
vs
id: string
name: string
startTime: int64
endTime: int64
sampleRate: int64
devices: list<item: struct<id: string, position: string, connectionId: string>>
snapshots: list<item: struct<time: int64, deviceData: struct<E4:B3:23:AD:5A:B2: list<item: double>, E4:B3:23:AD:22:26: list<item: double>, left_hand_virtual: list<item: double>, left_forearm_virtual: list<item: double>, right_hand_virtual: list<item: double>, right_forearm_virtual: list<item: double>, E4:B3:23:AD:24:0E: list<item: double>>>>
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
id: string
name: string
startTime: int64
endTime: int64
sampleRate: int64
devices: list<item: struct<id: string, position: string, connectionId: string>>
snapshots: list<item: struct<time: int64, deviceData: struct<E4:B3:23:AD:5A:B2: list<item: double>, E4:B3:23:AD:24:0E: list<item: double>, E4:B3:23:AD:22:26: list<item: double>, right_hand_virtual: list<item: double>, right_forearm_virtual: list<item: double>, left_hand_virtual: list<item: double>, left_forearm_virtual: list<item: double>>>>
vs
id: string
name: string
startTime: int64
endTime: int64
sampleRate: int64
devices: list<item: struct<id: string, position: string, connectionId: string>>
snapshots: list<item: struct<time: int64, deviceData: struct<E4:B3:23:AD:5A:B2: list<item: double>, E4:B3:23:AD:22:26: list<item: double>, left_hand_virtual: list<item: double>, left_forearm_virtual: list<item: double>, right_hand_virtual: list<item: double>, right_forearm_virtual: list<item: double>, E4:B3:23:AD:24:0E: list<item: double>>>>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.
Robotic Dataset
The dataset comprises 1,000+ hours of multimodal robot manipulation data collected from real-world environments, demonstrating manipulation tasks such as cleaning, laundry folding, and dishwashing performed by different robots. It contains synchronized sensor data from seven 9-axis IMU units attached to the robot arms, forearms, and chest, along with head-mounted videos and detailed trajectory recordings.
By utilizing this dataset, researchers can explore learning methods and robot manipulation techniques that enhance the ability of real robots to handle different objects and perform complex actions in real-world scenarios. - Get the data
Designed for robotic learning and model training, it provides data suitable for training models in robotic systems, foundation models, and real-world applications of humanoid robotics and robot manipulation.
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Dataset enables researchers and developers to build large-scale robot learning models, making it an essential resource for advancing robotic manipulation and real-world robotics research.
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