3D assets for better
sim-to-real transfer
The #1 cause of sim-to-real failure is inaccurate simulation data. Rigyd generates 3D assets with calibrated physics properties so policies trained in simulation actually work on real robots.
The problem
Why existing workflows fall short.
The sim-to-real gap is a physics gap
When simulation objects have wrong mass, friction, or collision geometry, trained policies fail on real hardware. The gap isn't the simulator — it's the data.
Domain randomization needs a good baseline
Randomizing around inaccurate physics values produces worse policies, not better ones. Domain randomization works best when centered on realistic parameters.
Real-world validation is expensive
Each sim-to-real iteration costs hardware time, engineer hours, and potential damage to expensive robots. Getting it right in simulation saves real-world cycles.
How Rigyd helps
AI-native infrastructure that automates the hard parts.
Calibrated physics baselines
Rigyd estimates mass within 15-20% of measured values and friction within 0.1 coefficient — providing accurate baselines for domain randomization.
Material-based estimation
AI identifies per-region materials (ceramic, aluminum, rubber) and maps them to a calibrated physical properties database. No guesswork.
Validated against research benchmarks
Physics estimation approach validated against NeRF2Physics (CVPR 2024) and GaussianProperty methodologies for mass and friction accuracy.
better real-world performance with physics-accurate training data
mass accuracy vs measured values
friction coefficient accuracy
Close the sim-to-real gap with better data
Start with physics-accurate assets and let domain randomization do the rest.
Starts at $29/month. 30 sim-ready objects included.
Explore more
SimReady for Isaac Sim
OpenUSD assets validated for NVIDIA Isaac Sim
Models for MuJoCo
Physics-accurate assets for robot learning
Assets for Gazebo
Simulation-ready models for ROS 2
Warehouse Simulation
50,000+ SKUs need physics properties
Humanoid Robots
Whole-body interaction training assets
Sim-to-Real Transfer
Close the gap with accurate physics data