Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
episode_index: int64
tasks: list<item: string>
length: int64
vs
episode_index: int64
stats: struct<observation.arm2_servo_node_status_data: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.arm2_servo_node_collision_velocity_scale_data: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.rosout_level: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.rosout_line: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, timestamp: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, frame_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, episode_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>>
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 559, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
episode_index: int64
tasks: list<item: string>
length: int64
vs
episode_index: int64
stats: struct<observation.arm2_servo_node_status_data: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.arm2_servo_node_collision_velocity_scale_data: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.rosout_level: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.rosout_line: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, timestamp: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, frame_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, episode_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>>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.
Universal Robot Arm Dataset (LeRobot Format)
This dataset contains robot manipulation data extracted from a ROS2 bag file, processed into LeRobot format for robot learning applications.
Dataset Contents
The dataset includes various sensor and control data from a robot arm:
- Joint States: Position, velocity, and effort of robot joints
- TF Transforms: Robot's kinematic state
- Robot Description: URDF and SRDF data
- Logging Information: Rosout messages
- Servo Node Status: Status information from the robot's servo nodes
- Controller Trajectory: Joint trajectory commands and states
Data Format
This dataset is in LeRobot format with:
- : Contains episode data in parquet format
- : Contains metadata and info files
- Compatible with LeRobot visualization and training tools
Usage
You can load this dataset using LeRobot:
Visualization
This dataset is compatible with the LeRobot visualizer for data exploration and analysis.
License
[Specify your dataset license here, e.g., MIT, Apache 2.0, etc.]
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