Physical AI

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Physical AI Datasets
Physical AI Datasets

Production-Ready Physical AI Datasets for Real-World Intelligent Systems

Physical AI demands data that captures how intelligent systems perceive, understand, and interact with the physical world. OTS Data provides production-ready datasets designed for robotics, embodied AI, humanoid systems, autonomous machines, and real-world task learning. Our datasets are carefully collected, annotated, and structured to help teams train models that perform reliably across complex physical environments.

  • Robotics & Embodied AI
  • Multimodal Perception & Sensor Fusion
  • Manipulation, Motion & Task Learning
Physical AI
Physical AI

Available Datasets

Datasets marked Sample-Ready can be reviewed within days. Partner-Led collections are scoped to your physical AI use case, target capability, and deployment requirements.

Egocentric Human Activity Dataset

Use Case: Robot Learning / Human Behavior Understanding
Format: MP4 + JSON/Parquet
Count: 2,000–10,000 hours*

Request Data

Synchronized Multi-View Activity Dataset

Use Case: Cross-View Learning / Robot Imitation
Format: MP4/VRS + Calibration + JSON
Count: 500–3,000 hours*

Request Data

Hand-Object Interaction Dataset

Use Case: Robotic Manipulation / Grasp Planning
Format: MP4/RGB-D + JSON + Point Clouds
Count: 500K–5M frames* 

Request Data

Multi-Sensor Human Activity Dataset

Use Case:Multimodal Learning / Sensor Fusion
Format: MP4 + WAV + CSV/Parquet
Count: 1,000–8,000 hours*

Request Data

Robotic Pick-and-Place Dataset

Use Case: Multimodal Learning / Sensor Fusion
Format: MP4 + WAV + CSV/Parquet
Count: 1,000–8,000 hours*

Request Data

Industrial Assembly & Tool-Use Dataset

Use Case: Industrial Robotics / Procedural Learning
Format: MP4 + JSON/Parquet + CAD Metadata
Count: 500–2,500 hours*

Request Data

VR Motion Capture Dataset

Use Case: Humanoid Learning / Motion Imitation
Format: CSV/JSON + BVH/FBX + Video
Count: 2,000–10,000 hours*

Request Data

Long-Horizon Task Demonstration Dataset

Use Case: Home Robotics / Task Planning
Format: MP4 + JSON/Parquet + Task Graphs
Count: 500–3,000 hours*

Request Data

Agricultural Robotics Vision Dataset

Use Case: Agricultural Robotics / Crop Perception
Format: JPEG/MP4 + COCO JSON + Depth
Count: 250K–2M frames*

Request Data

*Volumes shown are indicative and can be scaled based on project requirements. Images are representative and may not reflect actual dataset samples. Request a sample to review the available dataset media.

Compliance
Compliance

Security & Compliance

HIPPA
ISO 9001 : 2015
SOC 2 Type ll
ISO 27001
GDPR
Accurate Data
Accurate Data

Why Choose Us?

Real-World Physical AI Data

Datasets capture real-world environments, human actions, objects, and physical interactions to support embodied AI and robotics training.

Built for Your Robot & Use Case

Customize datasets by robot morphology, sensors, environment, task, modality, and annotation requirements.

Privacy & Safety by Design

Data is carefully de-identified and collected with privacy, safety, and responsible AI requirements in mind.

Human-Validated Data Quality

Expert review and quality-control processes help ensure accurate annotations, consistent data, and reliable training inputs.

Frequently Asked Questions
Frequently Asked Questions

Frequently Asked Questions

Physical AI datasets contain real-world data that helps AI systems perceive environments, understand physical interactions, and learn actions such as navigation, manipulation, assembly, and motion.
Our collection includes robotics, humanoid motion, hand-object interaction, multimodal sensor data, pick-and-place, industrial assembly, bimanual manipulation, and agricultural robotics datasets.
Yes. Partner-led datasets can be scoped around your robot morphology, sensors, environment, target tasks, and specific capability requirements.
Depending on the dataset, formats can include RGB/RGB-D video, JSON, Parquet, point clouds, trajectories, depth data, calibration data, CAD metadata, and robot-specific formats. Annotations may include poses, actions, object states, grasp phases, task steps, and trajectories.
Select a dataset and click Request Data. Sample-ready datasets can typically be reviewed within days, while partner-led collections are scoped according to your project requirements.