Real-World Robotics Data
Atlas collects the real-world data robots need to learn.
We build specialized multimodal datasets for robotics teams training world models, vision-language-action models, and embodied AI systems.
First sample set is free for qualified robotics teams.
01 — The Problem
Robotics is entering its foundation model era. The data layer is still missing.
Robotics teams need more than internet video. They need real-world trajectories, edge cases, failures, recoveries, object interactions, and multimodal signals captured from environments where robots will actually operate.
Sparse interaction data
Robots need examples of actions, consequences, failures, and recoveries — not just passive video.
Poor environment coverage
Useful robot learning requires diverse physical settings, workflows, objects, lighting, surfaces, and human behavior.
Hard-to-source edge cases
The highest-value data often comes from rare events, failed attempts, and recovery sequences.
02 — What Atlas Collects
Specialized data for embodied intelligence.
Human demonstrations
Task walkthroughs, object handling, manipulation, and workflow demonstrations.
Failure and recovery
Deliberate mistakes, correction sequences, retries, and recovery paths.
Multimodal capture
Video, depth, audio, position, force, tactile, and sensor-aligned data where available.
Environment coverage
Homes, workshops, factories, retail spaces, kitchens, warehouses, and specialized workspaces.
Edge-case tasks
Occlusion, clutter, awkward angles, lighting variation, object ambiguity, and unusual task setups.
Custom task bounties
Atlas can recruit contributors to complete specific data collection tasks.
03 — Process
From task spec to usable training data.
04 — Why Atlas
Built for the next generation of robot learning.
World models and VLA systems need data that captures how the physical world changes over time. Atlas focuses on informative trajectories, not generic footage.
05 — Who It's For
For teams building robots that need to operate in the real world.
Humanoid robotics teams
General-purpose manipulation, locomotion, and whole-body control.
Warehouse and logistics robotics teams
Picking, placing, sorting, and navigation in complex structured environments.
Manipulation and dexterity researchers
Fine motor tasks, tool use, and contact-rich interactions.
World model and VLA research teams
Scalable pretraining data for foundation models grounded in physical dynamics.
06 — Example Requests
Example requests Atlas can fulfill.
Record 100 examples of humans folding, failing, and refolding clothing.
Capture kitchen manipulation tasks from multiple camera angles.
Collect recovery sequences when objects slip, fall, or are misplaced.
Source warehouse picking examples in cluttered shelves.
Capture human movement around tools, doors, drawers, handles, and containers.
Build a dataset of object interaction under different lighting and occlusion conditions.
07 — Get Started
Need specialized robotics data?
Send Atlas a task spec. We'll return a sample dataset so your team can evaluate quality before committing.