Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    ReadTimeout
Message:      (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 39f2fa88-06d8-46c5-b4c3-eb870284c993)')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 353, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 278, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1781, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1663, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1620, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1018, in get_module
                  data_files = DataFilesDict.from_patterns(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 690, in from_patterns
                  else DataFilesList.from_patterns(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 593, in from_patterns
                  origin_metadata = _get_origin_metadata(data_files, download_config=download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 507, in _get_origin_metadata
                  return thread_map(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/contrib/concurrent.py", line 69, in thread_map
                  return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/contrib/concurrent.py", line 51, in _executor_map
                  return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/std.py", line 1169, in __iter__
                  for obj in iterable:
                File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 609, in result_iterator
                  yield fs.pop().result()
                File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 446, in result
                  return self.__get_result()
                File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 391, in __get_result
                  raise self._exception
                File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 58, in run
                  result = self.fn(*self.args, **self.kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 486, in _get_single_origin_metadata
                  resolved_path = fs.resolve_path(data_file)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
                  repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
                  self._api.repo_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2704, in repo_info
                  return method(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2561, in dataset_info
                  r = get_session().get(path, headers=headers, timeout=timeout, params=params)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 602, in get
                  return self.request("GET", url, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 589, in request
                  resp = self.send(prep, **send_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 703, in send
                  r = adapter.send(request, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 93, in send
                  return super().send(request, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/adapters.py", line 635, in send
                  raise ReadTimeout(e, request=request)
              requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 39f2fa88-06d8-46c5-b4c3-eb870284c993)')

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.

Dataset Description:

PhysicalAI-Robotics-Manipulation-SingeArm is a collection of datasets of automatic generated motions of a Franka Panda robot performing operations such as block stacking, opening cabinets and drawers. The dataset was generated in IsaacSim leveraging task and motion planning algorithms to find solutions to the tasks automatically [1, 3]. The environments are table-top scenes where the object layouts and asset textures are procedurally generated [2].
This dataset is available for commercial use.

Dataset Contact(s):

Fabio Ramos ([email protected])
Anqi Li ([email protected])

Dataset Creation Date:

03/18/2025

License/Terms of Use:

cc-by-4.0

Intended Usage:

This dataset is provided in LeRobot format and is intended for training robot policies and foundation models.

Dataset Characterization

Data Collection Method

  • Automated
  • Automatic/Sensors
  • Synthetic

The dataset was generated in IsaacSim leveraging task and motion planning algorithms to find solutions to the tasks automatically [1]. The environments are table-top scenes where the object layouts and asset textures are procedurally generated [2].

Labeling Method

  • Not Applicable

Dataset Format

Within the collection, there are six datasets in LeRobot format panda-stack-wide, panda-stack-platforms, panda-stack-platforms-texture, panda-open-cabinet-left, panda-open-cabinet-right and panda-open-drawer.

  • panda-stack-wide
    The Franka Panda robot picks up the red block and stacks it on top of the green block. panda-stack-wide
    • action modality: 7d, 6d relative end-effector motion + 1d gripper action
    • observation modalities:
      • observation.state: 53d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera output stored as mp4 videos
  • panda-stack-platforms
    The Franka Panda robot picks up a block and stacks it on top of another block in a table-top scene with randomly generated platforms. panda-stack-plaforms
    • action modality: 7d, 6d relative end-effector motion + 1d gripper action
    • observation modalities:
      • observation.state: 81d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera RGB output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera RGB output stored as mp4 videos
  • panda-stack-platform-texture
    The Franka Panda robot picks up a block and stacks it on top of another block in a table-top scene with randomly generated platforms and random table textures. panda-stack-plaforms-texture
    • action modality: 8d, 7d joint motion + 1d gripper action
    • observation modalities:
      • observation.state: 81d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera RGB output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera RGB output stored as mp4 videos
      • observation.depths.world_camera: 512x512 world camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
      • observation.depths.hand_camera: 512x512 wrist-mounted camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
  • panda-open-cabinet-left
    The Franka Panda robot opens the top cabinet of a randomly generated cabinet from left to right. panda-open-cabinet-left
    • action modality: 8d, 7d joint motion + 1d gripper action
    • observation modalities:
      • observation.state: 81d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera RGB output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera RGB output stored as mp4 videos
      • observation.depths.world_camera: 512x512 world camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
      • observation.depths.hand_camera: 512x512 wrist-mounted camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
  • panda-open-cabinet-right The Franka Panda robot opens the top cabinet of a randomly generated cabinet from right to left. panda-open-cabinet-right
    • action modality: 8d, 7d joint motion + 1d gripper action
    • observation modalities:
      • observation.state: 81d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera RGB output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera RGB output stored as mp4 videos
      • observation.depths.world_camera: 512x512 world camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
      • observation.depths.hand_camera: 512x512 wrist-mounted camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
  • panda-open-drawer
    The Franka Panda robot opens the top drawer of a randomly generated cabinet. panda-open-drawer
    • action modality: 8d, 7d joint motion + 1d gripper action
    • observation modalities:
      • observation.state: 81d, including proprioception (robot joint position, joint velocity, end-effector pose) and object poses
      • observation.images.world_camera: 512x512 world camera RGB output stored as mp4 videos
      • observation.images.hand_camera: 512x512 wrist-mounted camera RGB output stored as mp4 videos
      • observation.depths.world_camera: 512x512 world camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m
      • observation.depths.hand_camera: 512x512 wrist-mounted camera depth output stored as mp4 videos, where 0-255 pixel value linearly maps to depth of 0-6 m

Dataset Quantification

Record Count

  • panda-stack-wide
    • number of episodes: 10243
    • number of frames: 731785
    • number of RGB videos: 20486 (10243 from world camera, 10243 from hand camera)
  • panda-stack-platforms
    • number of episodes: 17629
    • number of frames: 1456899
    • number of RGB videos: 35258 (17629 from world camera, 17629 from hand camera)
  • panda-stack-platforms-texture
    • number of episodes: 6303
    • number of frames: 551191
    • number of RGB videos: 12606 (6303 from world camera, 6303 from hand camera)
    • number of depth videos: 12606 (6303 from world camera, 6303 from hand camera)
  • panda-open-cabinet-left
    • number of episodes: 1512
    • number of frames: 220038
    • number of RGB videos: 3024 (1512 from world camera, 1512 from hand camera)
    • number of depth videos: 3024 (1512 from world camera, 1512 from hand camera)
  • panda-open-cabinet-right
    • number of episodes: 1426
    • number of frames: 224953
    • number of RGB videos: 2852 (1426 from world camera, 1426 from hand camera)
    • number of depth videos: 2852 (1426 from world camera, 1426 from hand camera)
  • panda-open-drawer
    • number of episodes: 1273
    • number of frames: 154256
    • number of RGB videos: 2546 (1273 from world camera, 1273 from hand camera)
    • number of depth videos: 2546 (1273 from world camera, 1273 from hand camera)

Total storage: 15.2 GB

Reference(s):

[1] @inproceedings{garrett2020pddlstream,
    title={Pddlstream: Integrating symbolic planners and blackbox samplers via optimistic adaptive planning},
    author={Garrett, Caelan Reed and Lozano-P{\'e}rez, Tom{\'a}s and Kaelbling, Leslie Pack},
    booktitle={Proceedings of the international conference on automated planning and scheduling},
    volume={30},
    pages={440--448},
    year={2020}
}

[2] @article{Eppner2024,
    title = {scene_synthesizer: A Python Library for Procedural Scene Generation in Robot Manipulation},
    author = {Clemens Eppner and Adithyavairavan Murali and Caelan Garrett and Rowland O'Flaherty and Tucker Hermans and Wei Yang and Dieter Fox},
    journal = {Journal of Open Source Software}
    publisher = {The Open Journal},
    year = {2024},
    Note = {\url{https://scene-synthesizer.github.io/}}
}

[3] @inproceedings{curobo_icra23,
    author={Sundaralingam, Balakumar and Hari, Siva Kumar Sastry and
        Fishman, Adam and Garrett, Caelan and Van Wyk, Karl and Blukis, Valts and
        Millane, Alexander and Oleynikova, Helen and Handa, Ankur and
        Ramos, Fabio and Ratliff, Nathan and Fox, Dieter},
    booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},
    title={CuRobo: Parallelized Collision-Free Robot Motion Generation},
    year={2023},
    volume={},
    number={},
    pages={8112-8119},
    doi={10.1109/ICRA48891.2023.10160765}
}

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report security vulnerabilities or NVIDIA AI Concerns here.

Downloads last month
821

Collection including nvidia/PhysicalAI-Robotics-Manipulation-SingleArm