Handheld
FastUMI
Robot manipulation imitation learning
Approximately 10,000 handheld demonstrations across 22 domestic tasks, pairing GoPro video with tracked end-effector trajectories.
Access links
Primary places to inspect, download, read about, or reproduce the dataset.
Quick facts
- Vehicle type
- Handheld
- Environment
- Indoor
- Data origin
- Real-world
- Sensor count
- 1
- Ground truth
- Not reported
- Calibration
- Not reported
- Annotations
- Not reported
Sensor overview
High-level sensor availability before the detailed sensor records below.
Ground truth
Reference scope, method, rate, coverage, and provenance.
Calibration and synchronization
Reported calibration level, reproducibility signals, and supporting notes.
- Level
- Not reported
- Processed parameters
- Not reported
- Raw calibration data
- Not reported
- Calibration targets
- Not reported
Calibration data
Calibration reproducibility details are not reported.
Notes
Not reportedKnown or intentional limitations
Reported constraints and characteristics to check before using the dataset.
Wired data transfer constrains portability and field use.
Cameras
gopro
- Model
- Gopro Hero9
- Setup
- Mono
- Count
- 1
- Effective cameras
- 1
- Modality
- Rgb
- Resolution
- Not reported
- Rate
- 20 Hz
- Shutter
- Not Reported
- Lens type
- Fisheye
- HFOV
- Not reported
- VFOV
- Not reported
- Notes
- GoPro video paired with T265 pose estimates after 20 Hz subsampling. Acquisition example is 60 fps; released dimensions need verification. T265 raw images and IMU are not established release streams.
IMUs
GNSS
LiDAR
Radar
Pitot tube
Additional sensors
Annotations
Reported annotation availability and task support.
- Availability
- Not reported
- Format
- Not reported
- Class count
- Not reported
Citation
Citation key and BibTeX kept at the end of the page for reference.
Dataset corrections
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