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Documentation Index

Fetch the complete documentation index at: https://docs.cyberwave.com/llms.txt

Use this file to discover all available pages before exploring further.

Cyberwave turns every environment into a runnable simulation. Hit Simulate in the editor, or flip the SDK into sim mode — same scene, same twins, same code: 
from cyberwave import Cyberwave

cw = Cyberwave()
cw.affect("simulation")

robot = cw.twin("the-robot-studio/so101")
robot.joints.set("shoulder_pan", 45, degrees=True)   # runs against the virtual twin
When you’re done, cw.affect("live") points the same code at the real robot. No rewrites, no second SDK, no second environment.

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Why simulate?

Develop at code speed

Tweak a policy, re-run, see the result in the viewport — no robot, no lab, no waiting on hardware.

CI for robotics

Run the same scene headlessly in CI. Catch regressions in motion planners, perception, and controllers before they ship.

Train models

Use simulation rollouts to train and evaluate VLAs and RL policies on the same twins you’ll deploy on.

Synthetic data

Render camera streams, depth, and joint states from any environment to bootstrap datasets when real-world data is scarce.

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Simulation engine agnostic

Set up your environment once. Cyberwave handles the export to each backend so you can pick the right tool for the job without re-modeling anything.

Playground

Browser-based, runs on your machine’s compute. Best for fast iteration.

MuJoCo

High-fidelity, contact-rich physics. Best for RL, evaluation, and reproducible sim sweeps.

Isaac Sim

GPU-accelerated photoreal simulation. Coming soon.
Each twin advertises which backends it supports — see Simulator compatibility to control which simulators an asset or twin can participate in.

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Powered by the twin catalog

There’s no separate “simulation setup” step. Physics, kinematics, sensors, and collision geometry are read straight from the digital twins you dropped into the environment — every twin in the catalog ships with a URDF and inertial data ready to simulate. Add a twin → it’s instantly simulatable. Swap a SO-101 for a UR7e → the physics update on the next run.

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The two simulators today

Open any environment in the editor and click Simulate in the top bar.

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Playground — instant browser physics

Playground is a lightweight rigid-body simulator that runs entirely in your browser, using your machine’s compute. There’s nothing to install and nothing to wait for — it’s running the moment the page loads.
  • Fastest feedback loop — change a joint target in code, see the twin move in the viewport.
  • Great for sanity checks — verify motion plans, joint limits, and basic collisions before going live.
  • Works offline from cloud compute — every browser is its own simulator.
from cyberwave import Cyberwave

cw = Cyberwave()
cw.affect("simulation")          # subsequent commands run in Playground / MuJoCo

arm = cw.twin("the-robot-studio/so101")
arm.joints.set("shoulder_pan", 30, degrees=True)
arm.joints.set("elbow_flex",   -45, degrees=True)

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MuJoCo — contact-rich physics, your way

Need real grasps, friction, and reproducible RL sweeps? Cyberwave one-click-exports any environment to MuJoCo, two ways:

Export and run anywhere

Download a self-contained MuJoCo scene (XML + meshes) and run it on your laptop, your cluster, or your CI runner. Backed by the environment MuJoCo export API.

Run in the Cyberwave cloud

Kick off a MuJoCo simulation from the editor and stream results straight back into the browser viewport — no local install required.
All twins in the environment must be marked MuJoCo-compatible before a remote run starts — see how the compatibility gate works.

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See simulation in action

Autonomous rover inspection

Build and run an AI-driven inspection mission in a fully simulated environment.

Train a VLA with SO-101

Collect data, train a vision-language-action model, and validate in sim before touching hardware.

Go2: digital to physical

Configure a Unitree Go2 in simulation, then flip the same code onto the real robot.

Sandwich-making robot (SmolVLA)

Train, evaluate, and iterate a manipulation policy with simulation in the loop.