Generate the worlds.
Harden the runtime.
Titan Matrix is the simulation and synthetic-data platform for Titan Core OS. It routes one scenario spec to multiple world backends, injects failures, runs the real runtime in sim, and emits training and certification evidence.
Sim, synthetic data,
and release evidence.
The platform exists to find runtime failures before customers do: generate worlds, run Titan Core OS, observe outcomes, export datasets, and turn regressions into CI-blocking evidence.
Two-Source World Router
A Scenic-flavored scenario spec can target game-engine worlds, video-model augmentation, or high-throughput MJX runs.
Failure Injection
Sensor, actuator, comms, compute, adversarial, and impossible-physics failures are declarative, composable, and replayable.
Cycle-Accurate Titan Core OS
The same Titan Core OS binary runs in sim and on metal. HAL swaps real drivers for sim drivers without recompiling the runtime.
Deterministic Export
Every run emits a seed, asset manifest hash, MCAP recording, and LeRobotDataset v3 episode for analysis and training.
CI Regression
Curated scenario suites run on Titan Core OS changes and gate merges against latency, safety, recovery, and mission metrics.
Coverage Analytics
Reports show ODD coverage, failure-mode density, form-factor spread, and release-over-release regression budgets.
One scenario spec.
Multiple worlds.
Researchers author once in a Titan DSL inspired by Scenic. Matrix compiles that scenario into backend-specific worlds while preserving seeds, constraints, assets, and expected observations.
Game-engine path
Photoreal USD assets, AV scenarios, and lightweight ROS 2-native development environments behind one backend API.
Video-model path
Game-engine output becomes photoreal video conditioned on RGB, depth, and segmentation for rare visual conditions.
MJX path
High-throughput RL and sovereign customer workloads keep a non-NVIDIA path active for training and air-gapped sites.
Same binary.
Different drivers.
Titan Matrix does not validate a simplified model of Titan Core OS. It boots the runtime, uses the same ROS 2 + Zenoh bus and FFAL contracts, then swaps hardware drivers for deterministic sim drivers through the HAL.
Connected and disconnected behavior is tested end-to-end: link loss, telemetry buffering, override denial, resync replay, and audit attribution run through the same harness as hardware.
Scenario DSL
ODD axes, actors, terrain, weather, mission, seed
Backend compiler
Isaac, CARLA, gz-sim, Cosmos augmentation, or MJX
Titan Core OS runtime
Same scheduler, FFAL, TMO, and Core Command Link
Evidence export
MCAP, LeRobot v3, coverage report, regression status
Failure modes are
first-class scenario code.
Any scenario can combine multiple injected failures and replay them deterministically. Matrix is built for the cases field data has not produced yet.
Sensor degradation
Drop, freeze, noise, bias, occlusion, and adversarial perturbation
Actuator failure
Joint lock, torque loss, latency, deadband, and partial authority
Comms denial
Link loss, jitter, packet drop, jamming, and network partition
Compute saturation
Deadline misses, CPU throttling, frame drops, and memory pressure
Adversarial inputs
Physics-aware patch attacks and targeted perception failures
Impossible physics
Gravity flip, clock skew, NaN injection, and frame-rate jitter
Same loop.
Second world.
The normal loop is Titan Command Center directing machines that run Titan Core OS in the real world. Matrix adds a second place for the exact same loop to run: the same OS, booted in a virtualized world, controlled from the same console. Three ways to mix them:
The real world.
Machines run missions on real sites in real time. This is the default — and everything Matrix does exists to make this mode safer and smarter.
Everything simulated.
Titan Command Center flips to virtual mode and the whole fleet lives inside Matrix — same Titan Core OS, same missions, same alerts, no hardware at risk. Rehearse, train, and validate releases at will.
Real sensors, virtual world.
The virtual world is constructed from what the real fleet senses: the site your machines mapped yesterday becomes today's rehearsal world. Real telemetry keeps the simulation honest — and the simulation keeps getting more realistic as the fleet works.
The clock is a parameter.
In the field, a ten-hour patrol takes ten hours. In Matrix, time runs as fast as compute allows — a season of missions compresses into an afternoon. That speed is why the loop runs here first: every mission profile, every release, every operator drill gets years of experience before the field supplies its first hour.
Matrix has no interface.
Titan Command Center is the interface.
A machine inside Titan Matrix is not an emulation — it is a real Titan Core OS instance whose hardware layer happens to be a simulator. It boots the same runtime, loads the same skills, speaks the same Core Command Link, and reports to the same Titan Command Center. The console cannot tell the difference — which is exactly the point.
One fleet, two worlds
Field machines live in reality; virtual machines live in Matrix. Both appear in the same fleet view, run the same missions, and raise the same alerts — only the world underneath differs.
Operators train on the real thing
Mission rehearsal, incident drills, and operator onboarding run against the production console with simulated machines — not a training mock that diverges from the tool they'll actually use.
The control plane gets validated too
Every simulated mission exercises Titan Command Center itself — intents, overrides, alerts, resync. Releases are validated against the actual control plane, end to end.
Every run leaves
a replayable trail.
A Matrix job is only useful if another engineer can reproduce it later. The platform pins every input and exports the artifacts needed for model training, QA review, and customer evidence packs.
2.4M
scenario-ticks / day
6
failure categories
3
form factors
<=5%
timing deviation target
Scenario seed
Deterministic replay key shared across every backend
Asset manifest
Hash-pinned USD assets, configs, maps, and generated media
MCAP recording
Native robot telemetry, decisions, latencies, and recovery events
LeRobotDataset v3
Episode-grouped export for training, review, and FiftyOne ingestion