wwsim.

Remote Drone Simulation Orchestrator

Fly your autonomy
stack in seconds.

wwsim composes a versioned Gazebo world with a versioned vehicle profile, launches it on a remote GPU, and hands you a one-paste QGroundControl connection — no firewalls, no NAT, no wasted spend.

env × vehicle · MAVLink proxy · deterministic mode · auto-shutdown

The model

A simulation is environment × vehicle.

Two orthogonal axes, each versioned in its own repository. Swap the drone to see how an airframe handles a scene. Swap the world to see how an autonomy stack handles terrain. Neither copy-pastes the other.

Environment

The world

  • Terrain & scene objects
  • Weather, wind, lighting
  • Optional scoring function
×
Vehicle

The hardware

  • Airframe, motors, battery
  • Sensor stack
  • Autopilot params & overlays

Capabilities

Everything between an idea and a flown experiment.

Two versioned registries

Pick a Gazebo environment and a vehicle profile from independent registries — each a private GitHub repo, pinned to a git tag. A sim launched today is byte-identical six months from now.

Launched in seconds

A composed simulation provisions on a remote RTX-class GPU and is ready before you have switched windows. A warm pool makes hot launches near-instant.

One paste into QGC

No firewalls, no NAT, no raw UDP. Every sim returns a single TCP connection string that QGroundControl and Mission Planner accept as-is.

Companion compute

Attach your autonomy or navigation image as a second container, pre-wired to the MAVLink endpoint and sensor topics — isolated from every orchestrator credential.

Deterministic mode

Pin a seed and a fixed sensor-noise profile. Two runs of the same env, vehicle, and autonomy image produce identical traces — the signal your experiments optimize against.

Reproducible artifacts

Every sim ends with a bundle: telemetry log, parameter dump, exact env and vehicle manifests, optional rosbag and scorecard. Downloadable from the dashboard.

How it works

Four steps, fully reproducible.

01

Compose

Choose an environment and a vehicle profile. The orchestrator resolves both manifests, checks the vehicle satisfies the env, and records the exact refs.

02

Launch

A remote GPU pod boots the runtime — SITL, Gazebo, MAVLink router — and, optionally, your companion autonomy container.

03

Fly

Paste the connection string into QGroundControl or Mission Planner and fly. Telemetry streams to the dashboard in real time.

04

Compare

On stop, collect the artifact bundle. Same env, vehicle, and seed, every time — so two algorithm runs are actually comparable.

Built for autonomy iteration

Companion compute, deterministic seeds, and artifact bundles are first-class — so an algorithm change is something you can measure, not just observe.

Guardrails

Secure and accountable by default.

Compose a sim. Fly it. Compare the run.

Sign in with an approved account to launch your first simulation.

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