03 / Simulation & synthetic data
Real-world detail.
Room to test variations.
Bring your real environment and robot task into a simulation pilot built around training and evaluation.
Seeking pilot partners · Service in development
High-fidelity simulation
Fidelity where
the task needs it.
The details that matter depend on the problem. Geometry and sensor views may be central to one task. Another may depend on mass, friction, articulation or contact behavior. We define that requirement with your team.
- 01
Capture the environment
Scope imagery, geometry and physical measurements for your existing simulation workflow.
- 02
Build a bounded scenario
Define the assets, initial conditions and task variations that support your training goals, with interfaces and engineering scope agreed first.
- 03
Compare with real behavior
Test the simulated behavior against a physical reference to measure how well it represents your task.
Before collection or delivery
Define a
useful result.
A pilot specification built around your task, with clear goals for the first sample or workplace trial.
- Target workflow
- Simulator, robot model, controllers and required asset formats.
- Relevant fidelity
- Geometry, sensor appearance and task-critical physical properties.
- Scenario definition
- Objects, initial conditions, variations and outcome measures.
- Validation plan
- Reference measurements and separate real-world tests where needed.
The connection
More variation. A clear test of usefulness.
Synthetic augmentation may expand a suitable set of demonstrations or scenarios. In a pilot, we define compatible inputs and compare the result against a baseline on separate tests.
A few useful details
Questions
before a pilot.
Are you building a general-purpose simulator?
No. We focus on task-specific capture, assets and simulation environments that fit your existing workflow.
What does high fidelity mean here?
It means representing the visual and physical details that matter to a particular task. We specify the required properties and how to validate them in the pilot.
Will synthetic data improve our model?
We design the pilot to measure the impact on your model, using a baseline, useful variations and a separate evaluation set. The results guide the next training step.
Start a conversation
What does your simulation need to reproduce?
Start with the task, your simulation workflow and the real-world behavior you need to represent.