Error code:   ConfigNamesError
Exception:    TypeError
Message:      List.__init__() got an unexpected keyword argument 'description'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 605, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2031, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1876, in from_dict
                  obj = generate_from_dict(dic)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1463, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1476, in generate_from_dict
                  return List(generate_from_dict(feature), **obj)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              TypeError: List.__init__() got an unexpected keyword argument 'description'

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.

FastUMI Pro – Multimodal Sample Dataset

Small-Scale Demonstration Data from the FastUMI Pro Multimodal Sensing System
(Only Dozens of Trajectories — Full Dataset Available Upon Request)

Project Homepage

📖 Overview

The FastUMI Pro Sample Dataset provides a public preview of the multimodal sensing capabilities of the FastUMI Pro data collection system.

This release contains only dozens of sample trajectories and is intended for:

System testing
Robotics and AI pipeline integration
Preliminary algorithm development
Demonstrating multimodal alignment and synchronization

Full-scale datasets are available upon request for research or enterprise collaboration.

📊 Data Specifications

Purpose: The following table is to provide users with an overview of the technical specifications of the dataset.

Data Type	Path	Shape	Type	Description
RGB Images	RGB_Images/Frames/*.mp4	(H, W, 3)	uint8	Multi-view RGB images
ToF PointClouds	ToF_PointClouds/PointClouds/*.pcd	variable	pcd	Time-of-Flight point clouds
Clamp Data	Clamp_Data/clamp_data_tum.txt	(N, 2)	float	Timestamp + clamp width
Merged Trajectory	Merged_Trajectory/merged_trajectory.txt	(N, 8)	float	Fused multi-sensor pose

🧭 Data Formats

All pose data (SLAM, Vive, fused) follow the same structure:

timestamp  x  y  z  qx  qy  qz  qw

Field	Description	Field	Description
timestamp	Unix timestamp	qx	Quaternion X component
x	Position X (meters)	qy	Quaternion Y component
y	Position Y (meters)	qz	Quaternion Z component
z	Position Z (meters)	qw	Quaternion W component

Coordinate System

To ensure correct visualization and control, all pose data adheres to the following right-handed coordinate system (World Frame).

Origin (0,0,0): Geometric center of the tracking base stations (World Frame).
🔴 X-Axis: Points Forward (the primary direction of manipulation).
🟢 Y-Axis: Points Right (relative to the workspace).
🔵 Z-Axis: Points Upward (opposite to the direction of gravity).

Visual reference for the coordinate system.

Tip: When using simulation environments like ROS or Isaac Gym, ensure your coordinate frame conventions match. You may need to apply a transformation if your framework uses a different "up" axis (e.g., Z-up vs. Y-up).

📸 How We Collect Data

We collect data using the FastUMI Pro hardware suite. This system integrates high-frequency sensors to capture comprehensive multimodal interaction data:

Visual: Industrial-grade RGB cameras.
Spatial: Time-of-Flight depth sensors for dense 3D reconstruction.
Haptic/State: Force-sensitive clamp sensors for precise gripper feedback.

📥 Download

huggingface-cli download FastUMIPro/example_data_fastumi_pro_raw \
  --repo-type dataset \
  --local-dir ./fastumi_sample/

Optional:

export HF_ENDPOINT=https://hf-mirror.com

⚠️ Dataset Scale Notice

This dataset contains only a small number of sample episodes and is not intended for large-scale training.

For full multimodal datasets or enterprise collaborations, please contact the FastUMI team.

📞 Contact

Lead: Ding Yan
Email: dingyan@lumosbot.tech
WeChat: Duke_dingyan

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