Key Features
Physics-Based Sensors
High-fidelity sensor models including FMCW LiDAR with Doppler. Full urban and aerial environments with configurable scenarios.
Multi-Platform Support
Simulation backends for both ground and aerial platforms with realistic physics and sensor models.
GPU Visualization
Real-time 3D rendering with developer tools for algorithm diagnostics, map inspection, and performance profiling.
Reproducible Runs
Containerized orchestration ensures identical simulation environments. Deterministic replay from recorded sensor data.
Technical Specifications
- Sensor Models
- FMCW LiDAR (with Doppler), ToF LiDAR, camera, IMU, GNSS
- Environments
- Urban, highway, aerial — fully configurable
- Orchestration
- Containerized, declarative manifests
- GPU Requirements
- NVIDIA CUDA-capable (RTX series recommended)
- Visualization
- GPU-accelerated real-time 3D rendering
Use Cases
Algorithm Development
Rapid iteration on perception algorithms with instant feedback. Test against diverse scenarios without physical hardware.
Regression Testing
Automated pipeline testing with deterministic replay. Catch regressions before they reach production.
Scenario Validation
Validate system behavior across edge cases — adverse weather, dynamic obstacles, sensor degradation — safely and repeatably.
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