Simulation-ready models for
MuJoCo

Convert 3D assets into models with accurate physics properties for MuJoCo. AI estimates mass, friction, contact parameters, and generates collision geometry automatically.

The problem

Why existing workflows fall short.

MuJoCo XML authoring is manual

Defining geoms, bodies, and joints with accurate physical parameters in MJCF XML requires domain expertise and per-object tuning.

Physics estimation guesswork

Estimating mass, friction, and contact parameters for arbitrary objects is time-consuming. Inaccurate values lead to unrealistic sim behavior.

Scaling object diversity

Training generalizable manipulation policies needs thousands of varied objects. Creating each one manually doesn't scale.

How Rigyd helps

AI-native infrastructure that automates the hard parts.

AI-powered contact parameters

Rigyd estimates friction, restitution, and condim values using material identification — calibrated for MuJoCo's contact model.

Accurate mass and inertia

Volume estimation combined with material density lookup produces mass and inertia values within domain randomization variance ranges.

Bulk object generation

Convert entire object datasets at once. Enterprise API supports high-throughput pipelines for building diverse training object sets.

97%

faster than manual physics annotation

15-20%

mass accuracy vs measured (within DR ranges)

$370K

saved per 1,000-object project

Build better MuJoCo training environments

Upload a 3D model and get physics-accurate assets for MuJoCo in minutes.

Starts at $29/month. 30 sim-ready objects included.