Xipotech
Digital twins• Synthetic data• HIL / SIL• Cloud-scale orchestration

Simulation & Test Design

High-fidelity scenario generation, synthetic data, and HIL/SIL validation, plus cloud-scale orchestration to run thousands of parameterised simulations in parallel, optimise robotic behaviours & operations, and deploy the best policies to the field.

From photoreal digital twins and accurate sensor models to CI-gated promotion, we de-risk field trials for vision, SLAM, and manipulation workloads.

Book a demo See AI-powered Object Tracking & Classification
Cloud-scale Simulation & Test Design schematic

How it works

  1. Model: build digital twins with photoreal scenes, terrain, and physics.
  2. Instrument: accurate sensor models (multi-camera, LiDAR, IMU, GNSS) with time-sync & noise.
  3. Generate: scenario and traffic agents with domain randomisation & edge-case libraries.
  4. Run at scale: Kubernetes orchestration sweeps parameters and replays logs in parallel.
  5. Score: KPIs for safety, coverage, accuracy, latency, energy, and wear.
  6. Optimise: search controllers/policies (Bayesian, RL, evolutionary) against KPIs.
  7. HIL/SIL: close the loop with hardware rigs and emulated sensors/actuators.
  8. Promote: CI gates deploy proven behaviours to field devices with audit trails.

Why cloud-scale simulation

Faster iteration
Run thousands of scenarios overnight to find robust policies.
Lower field risk
Catch regressions in sim before they become incidents on site.
Objective decisions
Compare algorithms by KPIs, not anecdotes or single runs.
Operational parity
Sensor noise, latency, and timing match edge deployments.
Repeatability
Deterministic seeds & versioned assets for exact replays.
Cost control
Autopilot GPU/CPU scaling and spot capacity to manage spend.

What you get

  • Scenario libraries, digital twins, and sensor model packs (multi-camera, LiDAR, IMU, GNSS).
  • Cloud-native runners (Kubernetes jobs) with parameter sweeps and log replay.
  • Automated KPI dashboards: accuracy, safety, throughput, energy, cost.
  • HIL/SIL rigs, wiring, and harnesses with documentation and CAD.
  • CI/CD templates to gate releases and deploy proven behaviours to the field.
KPIs that matter
Accuracy, safety, latency, cost
Kubernetes
Batch parallel jobs at scale
Edge parity
Timing & noise models aligned
Reproducible
Seeds, versions, audit trails

Tech highlights

ROS / ROS 2 pipelines
SIL with recorded bags; HIL with hardware bridges.
Sensor fidelity
Camera/LiDAR noise, rolling shutter, motion blur, timing.
Domain randomisation
Lighting, weather, clutter, materials, behaviours.
Policy search
Bayesian, evolutionary, and RL tuning against KPIs.
CI integration
Git triggers, artifact storage, & gated promotion.
Observability
Structured logs, traces, and per-run artefacts.

De-risk deployment with Simulation & Test Design

Stand up cloud-scale scenarios, validate with HIL/SIL, and roll out proven behaviours across your fleet.

Talk to our team Explore Agri-Robotics
Digital Twins
Synthetic Data
HIL / SIL
Kubernetes
CI / CD
Deploy with Confidence