OPEN SOURCE · HUMANOID SIMULATION
Give your humanoid
new ground.
Move beyond flat-floor tests. Build mixed terrain, connect your simulator, and see how a motion-tracking policy responds.
Experimental research tool · Newton MPM + Isaac Lab / MuJoCo
across the default map
exclusive terrain tiles
material combinations
curriculum levels
LATEST STUDY / REPORT UPDATED 21 SEP 2026
Training completed.
Stable tracking is still the goal.
Two matched 256-rollout experiments tested shallow-to-deep practice against direct training. Both missed the original-depth stability and tracking requirements.
Study complete · No checkpoint promoted · Research baseline retained
Original 14 cm soil · Three development motions · Seed 23 · 30 seconds per terrain family, with automatic resets. Neither candidate retained mud tracking accuracy or completed full references in every soil family.
The experiment
Frozen SONIC + a learned leg residual. Four environments, 50 Hz control, 2 cm MPM grid, original motion timing.
The failure analysis
Large pelvis tilt, tracking drift and difficult foot extraction. Reward conflict is one hypothesis; physics and practice distribution also matter.
The evidence
All twelve reward terms, PPO and actuator settings, soil parameters, reset events, source hashes, interrupted attempts and measured results.
01 / IN THE SIMULATOR
Watch the policy meet the terrain.
Archived 13 September frozen-teacher recordings at a 4 cm grid. These are not videos of the latest trained policies. Failures and resets remain visible.
Starts on sand + mud + rocks. Curriculum demotion and episode resets remain visible.
MODEL & MEASUREMENT
SONIC teacher / step 8,000
The strongest measured teacher in the available local checkpoint comparison. This is a frozen policy evaluation, not a terrain-trained success claim.
- Video
- 10 s · 25 fps
- Recorded env terminations
- See record
- Physics grid
- 4 cm · exploratory
- New native runs
- Receipts loading…
02 / ONE MAP, MANY CONDITIONS
Explore your next experiment.
A connected rigid map with localized material patches. Select a tile to inspect its composition and curriculum level.
Loading the generated map…
03 / DESIGNED TO CONNECT
Keep your simulator.
Add material interaction.
One shared terrain description connects rigid geometry, material simulation and motion-tracking evaluation. Start with exports; attach the live bridge when you need deformable contact.
Generate
Seeded terrain JSON
Rigid USD + MuJoCo XML
Couple
Newton advances materials
Your engine advances the robot
Evaluate / train
Per-env resets & curriculum
Policy metrics + surface replay
04 / FROM DEMO TO YOUR TASK
Start small. Build on evidence.
Map generation works on CPU. Live materials require the Newton GPU worker; native policy runs additionally need a compatible Isaac/SONIC installation and your model assets.
CPU-only geometry export. No teacher checkpoint or Isaac installation required.
Read the full integration guide ↗| Platform | Ready to use | What you bring |
|---|---|---|
| Newton | MPM materials, probes, surface reconstruction | Compatible CUDA GPU |
| MuJoCo | Rigid XML + live external-wrench bridge | Matching robot model and policy adapter |
| Isaac Sim / Isaac Lab | Shared USD, exclusive origins, resets, surfaces | Native installation and compatible task |
| SONIC | Frozen-policy eval + PPO warm start | Compatible TRL fork, weights and motion data |
Demonstrated
- Native two- and four-environment execution
- Selective resets preserve peer states
- Continuous surfaces from measured MPM samples
- Two completed 256-rollout adaptation arms with numerical checks
Still to establish
- Sand and mud calibration against real measurements
- Reliable deep-soil tracking and useful learning gains
- High-throughput training at large batch sizes
- General adapters beyond the tested SONIC fork
Water is excluded. Smooth surfaces improve the display, not the physics model. Importing USD or XML alone does not activate deformable materials.
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