EMBODIMENT-AGNOSTIC INTELLIGENCE
One robot brain. Many possible bodies.
We build high-level intelligence and reusable policies that understand goals, reason about action, and adapt their control to the body they inhabit.
Shared high-level brain
Policies adapt to each body
Humanoid
Mobile
Arm
The brain plans. The body executes.
Instead of learning a separate mind for every robot, a shared high-level brain works in an abstract action space: goals, objects, affordances, contact, and outcomes. Each embodiment exposes its own capabilities through an adapter layer.
High-level intent — understand the task and desired outcome.
Shared policies — select coordinated motion based on context.
Body adapter — map the policy to joints, sensors, and constraints.
A control stack designed for transfer
Every stage improves a common representation of action, making new bodies a matter of adaptation rather than starting again.
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Simulate broadly
Train across physics engines and randomized conditions to expose policies to more of the possible world.
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Learn in abstractions
Keep the high-level policy focused on what should happen—not the kinematics of a single robot.
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Adapt at the edge
Let each body contribute its sensors, actuators, and limits while the overall decision-making stays coherent.
The goal is not a better robot body. It’s a better robot mind.
An intelligence that carries its experience forward—no matter what body it wakes up in next.