Built with Meta's Muse Spark · Meta Global AI Developer Hackathon

Fix your robot before you spend a dollar.

RobotForge gives robot models a driving test before anyone trusts them. Describe a robot in words, a photo or a parts list — its simulated twin has to pass before you build or buy anything.

Illustration of a rugged four-wheel rover on a workbench
AI illustration (muse-image-1.0). The real robots in the app carry real, credited photos.
How it works

How the driving test works.

  1. 01

    Describe it

    Words, a photo, or a parts list.

  2. 02

    Muse Spark writes the spec

    The description becomes a spec sheet — numbers only.

  3. 03

    The app builds the twin

    The spec becomes a model (URDF/SDF), built in the Gazebo simulator.

  4. 04

    The gate runs the test

    The robot drives straight and turns. The gate compares odometry — where it thinks it went — with ground truth: where it actually went.

The verdict

Pass Distance error 5% or less, heading error 5° or less.

Marginal Between 5% and 10%.

Fail Over 10%, or over 10°. The gate names the spec numbers it suspects.

A physically impossible spec — ground clearance bigger than the wheel radius — is refused before the test runs.

Proof, from real runs

TurtleBot3 Burger — PASS. Distance off by 2.293%, heading by 1.421°.

Pathfinder — PASS.

Andino — FAIL. Heading off by 9.104°: its caster wheel drags in a turn.

A robot that has not run the test is marked NOT GATED.

Under the hood: Muse Spark → spec → deterministic URDF/SDF generation → Gazebo → odometry vs ground truth.

What a PASS proves — and what it doesn't →

Proof

Two recorded runs.

One earned a PASS. One was rigged to fail — and its own sensors couldn't tell.

Described in words, never drawnPass

Indoor Delivery Rover

One paragraph of plain English became a spec, a twin, and a measured PASS.

Drive error
0.398%
Turn error
3.653°
Fault injectionFail

Wheels 10% smaller than the paperwork

TurtleBot3 Burger with its physical wheels shrunk to 0.9× while odometry kept believing the spec. The robot's own sensors couldn't see it. The gate could.

Drive error
7.617%
Odometry vs truth
11.168%

Bars run 0–15: green passes, yellow is marginal, past it fails. Recorded in Gazebo Sim, headless, Oct 26, 2026.

All gate reports →
AI inside

Muse Spark reads, drafts and proposes. It never decides.

Reads

Robot photos, spec sheets and part labels become numbers, each marked ESTIMATED or DOCUMENT-READ.

Drafts

Plain words or a parts list become a full engineering spec.

Proposes fixes

When a check fails, it suggests a change. The checks accept or reject it, up to three rounds.

Not AI, on purpose

The engineering checks, the rover estimates, the URDF and twin, and the Gazebo verdict. Same answer every time.

Where Muse Spark works →

See a broken robot get fixed in one click.

Watch a broken spec get caught, fixed and re-tested — the whole loop in one run.

Run the demo →Open the app →
The one-click demo: the engineering checks flag a voltage mismatch and a clearance error, and the Forge loop fixes both in one round
The one-click demo, mid-run.