Robotic Data Services

Build the Data Your Physical AI Program Needs

Real-world data for robots, autonomous systems and Physical AI.

Training a machine to operate in the physical world requires more than a model. It requires the right environments. The right people. The right interactions. The right sensors. And enough high-quality data to turn intelligence into real-world capability.

Robotic Data designs, captures, processes and delivers real-world datasets for Physical AI — from an initial pilot to global-scale deployment.

What does your system need to learn?

Tell us what you're building. We'll help identify the data required to build it.

What are you trying to teach your system?

Every Physical AI program has a different data challenge.

Select the capability closest to what you're building.

NAVIGATE

Teach machines to understand where they are and move safely through the physical world.

High-fidelity spatial datasets for autonomous vehicles, mobile robots, drones and location-aware AI.

  • Street-level LiDAR
  • 360° imagery
  • Precision positioning
  • HD maps
  • Indoor mapping
  • Pedestrian environments
  • Localization datasets
  • Change detection
Explore Navigation Data

PERCEIVE

Give AI a richer understanding of the environments in which it will operate.

Capture roads, buildings, infrastructure, industrial facilities, campuses and complex real-world environments from multiple perspectives.

  • LiDAR
  • High-resolution imagery
  • Aerial imagery
  • Point clouds
  • Semantic features
  • 3D reconstruction
  • Gaussian Splats
  • Digital twins
  • Environmental context
Explore World Data

MANIPULATE

Teach robots how people interact with objects and perform physical tasks.

Capture real examples of human actions, object manipulation, movement and task completion.

  • Fine motor tasks
  • Object interaction
  • Pick-and-place activities
  • Tool use
  • Household tasks
  • Industrial tasks
  • Human demonstrations
  • Egocentric video
  • Motion capture
Explore Human Task Data

INTERACT

Help machines understand the people they'll work alongside.

Capture the signals Physical AI needs to understand human behavior, communication, intent and social interaction.

  • Human movement
  • Gestures
  • Speech
  • Conversation
  • Audio
  • Human-to-human interaction
  • Human-to-robot interaction
  • Behavioral context
  • Multi-person activities
Explore Human Interaction Data

SIMULATE

Turn reality into training environments.

Create detailed representations of real places, objects and interactions for simulation, synthetic-data pipelines, model evaluation and digital twins.

  • 3D environments
  • LiDAR
  • Digital twins
  • Gaussian Splats
  • Semantic datasets
  • Terrain models
  • Indoor environments
  • Street environments
  • Real-world validation datasets
Explore Simulation Data

SCALE

Move from a successful experiment to an enterprise data program.

We design and operate repeatable collection programs for organizations that need consistent data across cities, countries, populations or thousands of participants.

  • Multi-country collection
  • Participant recruitment
  • Large-scale sensor deployment
  • Repeatable collection protocols
  • Quality assurance
  • Data processing
  • Annotation and structuring
  • AI-ready delivery
Discuss a Scaled Data Program

Two data pillars. One physical world.

World Data — Teach Machines Where They Are

World Data creates the spatial intelligence machines need to perceive, localize, navigate and reason about real environments. Robotic Data combines multiple perspectives to create high-fidelity representations of the physical world.

Street-Level Data

Capture roads, cities and transportation environments using high-density LiDAR, high-resolution imagery and precision positioning. Available as custom worldwide collection programs or through Robotic Data's expanding SYMBO Network in the United States.

Ideal for

Autonomous vehicles · HD mapping · localization · infrastructure intelligence · change detection · digital twins · AI training

I Need Street-Level Data

Aerial Data

Capture entire sites, cities, regions or countries from above using fixed-wing aircraft, helicopters and drone platforms. Data products can include LiDAR, orthophotography, elevation models, surface models, terrain models and GIS-ready layers.

Ideal for

Drone autonomy · terrain intelligence · infrastructure mapping · digital twins · simulation · asset inventory · change detection

I Need Aerial Data

Indoor & Pedestrian Data

Capture the environments vehicles and aircraft cannot reach. Portable mapping platforms create high-detail representations of warehouses, factories, airports, hospitals, campuses, retail environments and transit facilities.

Ideal for

Humanoid robotics · AMRs · warehouse automation · indoor navigation · facility intelligence · simulation

I Need Indoor / Pedestrian Data

Human Data

Teach Machines What People Do

Useful robots must learn much more than geometry. They need to understand how humans move, communicate, manipulate objects, complete tasks and interact with their environment.

Robotic Data creates multimodal Human Data programs specifically for humanoid robots, embodied AI, foundation models and Physical AI — capturing people performing the tasks your machine needs to learn.

Egocentric videoThird-person videoMotion captureAudio and speechWearable sensorsLiDARVolumetric captureGaussian SplatsObject interactionsEnvironmental context

End-to-end programs including study design, participant recruitment, global collection, quality assurance and AI-ready dataset delivery.

World Data + Human Data

Build the Complete Context for Physical AI

The most capable intelligent machines won't experience people and environments separately. They'll experience them together.

A humanoid working in a warehouse must understand the building, the objects inside it, the people moving through it and the tasks those people perform.

An autonomous delivery system must understand streets, sidewalks, entrances, obstacles and human behavior. A service robot must understand the room around it — and the person asking it to do something.

World Data teaches machines where they are.

Human Data teaches machines what people do.

Together, they provide a richer real-world foundation for machines that need to perceive, reason and act.

From question to dataset

You Define the Capability. We Build the Data Program.

01

Define

What does the model, robot or autonomous system need to learn? We translate a capability requirement into a practical data specification.

02

Design

Environments, participants, tasks, geographies, sensor modalities, capture methodology, data structure and quality requirements.

03

Capture

Real-world collection using the appropriate combination of people, vehicles, aircraft, portable systems, sensors and environments.

04

Process

Captured data is structured, synchronized, quality assured and prepared around your technical requirements.

05

Deliver

Receive data in the formats required by your training, simulation, validation or production workflow.

06

Scale

Once the methodology works, we expand the program across participants, locations and countries.

Built to scale

Real-World Data Infrastructure for Enterprise Physical AI

26

Countries with delivered operations

100,000+

Hours of Human Data collected

250,000+

Human Data participant network

12+

Countries in the participant network

8+ Years

Supporting large-scale data programs

From one facility to an entire country.
From a pilot study to hundreds of thousands of human interactions.

Not sure what data you need?

Start With the Physical AI Data Assessment

You don't need to arrive with a finished specification. Tell us what you're building and what your system needs to learn. We'll identify the World Data, Human Data or multimodal collection approach most relevant to your program — instantly.

What happens next?

No Generic Sales Call.

Your assessment gives our team context before the conversation begins. We'll look at:

  1. The capability you're building
  2. What your system needs to learn
  3. The environments, people and interactions involved
  4. The appropriate data modalities
  5. The likely collection methodology and scale

Then, where there's a fit, we'll discuss the most practical route to a pilot or production program.

Your Model Can Only Learn From the World You Show It.

Give it better data.

World Data. Human Data. Built for Physical AI.

Already have a detailed specification?