Data Parameters & Standards
Industry-leading specifications ensuring your datasets are production-ready for robotics training
Quality Parameters
Precise technical specifications for each data modality to ensure optimal model training.
Vision Parameters
Resolution
4K (3840×2160) minimum
Frame Rate
30-60 FPS synchronized
Codec
H.264/H.265 lossless
Color Space
sRGB calibrated
Bitrate
100+ Mbps
Motion Capture Parameters
Skeleton Model
22+ joint points
Tracking Accuracy
±2cm spatial error
Temporal Resolution
120 Hz minimum
Hand Tracking
26 finger joints
Rotation Accuracy
±5 degrees
Robot State Parameters
Joint Angles
±0.1° accuracy
Sampling Rate
500 Hz minimum
Torque Measurement
±1% full scale
Gripper Force
±0.5N resolution
End-Effector Pose
6D (XYZ + rotation)
Temporal Parameters
Sync Precision
±1 millisecond
Timestamp Format
Unix epoch (ns)
Duration
5-60 minutes per clip
Continuous Recording
No drops allowed
Latency
<50ms end-to-end
Dataset Composition
Requirements
Minimum specifications for creating production-ready robotics datasets.
10-100+ hours
Dataset Hours
Depends on task complexity and diversity needs
5+ unique locations
Environment Diversity
Different lighting, backgrounds, and conditions
10+ different people
Performer Diversity
Various body types, skill levels, and demographics
15-20% of data
Failure Cases
Intentional failures to teach error recovery
50+ per variation
Repetitions
Multiple attempts of each task variant
10+ task variants
Variations
Different object sizes, positions, and conditions
Our Standards & Protocols
Comprehensive frameworks ensuring data quality, security, and usability.
Nferent Data Standard v1.0
Our proprietary standard for Physical AI datasets
- Multi-sensor synchronization protocol
- Standardized metadata schema
- Quality assurance checklist
- Privacy & anonymization guidelines
- Version control & lineage tracking
Calibration Protocol
Ensuring measurement accuracy across all sensors
- Camera intrinsic calibration (OpenCV)
- Camera extrinsic calibration (hand-eye)
- IMU calibration & bias correction
- Depth sensor calibration
- Temporal sync calibration
Privacy & Security
Protecting contributor and company data
- Face anonymization (automatic)
- PII removal protocols
- Encrypted data transfer (TLS 1.3)
- Secure storage (AES-256)
- Access control & audit logs
Labeling Protocol
Consistent, high-quality annotations
- Skill taxonomy standardization
- Action segmentation guidelines
- Object detection labeling
- Failure case documentation
- Multi-annotator consensus
Nferent Data Standard v1.0
Our proprietary standard combines industry best practices with robotics-specific requirements. Every dataset we deliver meets or exceeds these specifications.
- Multi-sensor synchronization protocol
- Standardized metadata schema
- Quality assurance checklist
- Privacy & anonymization guidelines
- Version control & lineage tracking
