Robotics and embodied AI · Uthana

Robotics and Embodied AI

Uthana's motion models generate structured, physically grounded human motion — the kind of data that robotics and embodied AI systems need to learn from. Start from text or video, get motion that can be retargeted across body plans and exported into simulation, training, or control workflows.

The challenge

Teaching robots to move like humans is a data problem

Humanoid and embodied AI systems need large, varied sets of human motion to learn from. But sourcing that motion through mocap or manual animation is slow and hard to scale.

Motion data is hard to scale

Mocap produces good data, but not at the volume or variety most training pipelines need.

Adapting across body plans is nontrivial

Human motion doesn't map directly to a robot's kinematics. Proportions, joint limits, and ground contact all need to be accounted for.

Tooling is fragmented

Generation, retargeting, format conversion, and simulation ingest often live in separate tools with manual handoffs between them.

How it works

Text or video in, robot-ready motion out

Describe a motion or provide a video reference. Uthana generates structured humanoid motion, retargets it to your robot's body, and exports it in the format your stack expects.

Step 1 — Describe or reference a motion

Start from a text prompt or a monocular video. Generate motion from a description, or extract it from footage.

Step 2 — Generate structured motion

Uthana produces temporally coherent, full-body humanoid motion — structured for downstream retargeting and use in control or training workflows.

Step 3 — Retarget to your robot's body

Map the motion onto your robot's kinematic structure. Uthana accounts for proportions, joint constraints, and contact behavior.

Step 4 — Export into your stack

Output in the format your pipeline needs — CSV, URDF, MJCF — for simulation, imitation learning, evaluation, demos, or internal tooling.

Why Uthana

What this gets you

Faster motion data, broader behavioral coverage, body-aware output, and direct pipeline integration.

Speed

Generate motion data in seconds

Create usable motion examples from text or video instead of relying solely on teleoperation, manual animation, or mocap cleanup.

Coverage

Broader behavioral range

Generate or extract locomotion, transitions, recovery motions, gestures, and task-specific actions across a wider range than manual methods typically cover.

Body-aware output

Motion shaped to your robot

Go beyond generic human motion. Retarget outputs to your robot's proportions, joint limits, and kinematic structure.

Integration

API-first, pipeline-ready

Bring motion generation and export directly into your data pipelines, simulators, evaluation tools, or labeling workflows via the API.

Get started

Bring Uthana into your robotics or embodied AI workflow

API access for text-to-motion and video-to-motion. Retargeting to custom body plans. Batch generation for dataset creation. Enterprise options for custom models, data isolation, and deeper integration.