C-Radiant

Electro-optic and infrared renderings in MuSES achieve global benchmark accuracy through a stepwise workflow – beginning with heat sources such as engines, exhaust, bearings, and electronics, followed by an in-band diffuse radiosity solution. Then place your sensor at range and render multi-bounce, spectrally-summed radiance values, with DeltaT-RSS contrast metrics. Sensor response curve handy? Import it and see what you’ve been missing. With MuSES, you have reality at your fingertips. Because MuSES covers physics all the way back to heat sources and environmental loads, you can manage thermal signature contrast and evaluate control kits for low observable design in any global location. Heat shields, cooling schemes, and even camo surface treatments can be tested and evaluated for in-band radiance, replete with atmospheric attenuation along sensor line-of-sight. Triage and prioritize your engineering with MuSES early in the development cycle.

Parallel Domain Replica Sim enables the creation of high-fidelity, fully annotated, simulation-ready environments from users’ own captured data (photos, videos, scans). With PD Replica, you can generate near-pixel-perfect reconstructions of real-world scenes, transforming them into virtual environments that preserve visual detail and realism. PD Sim provides a Python API through which perception, machine learning, and autonomy teams can configure and run large-scale test scenarios and simulate sensor inputs (camera, lidar, radar, etc.) in either open- or closed-loop mode. These simulated sensor feeds come with full annotations, so developers can test their perception systems under a wide variety of conditions, lighting, weather, object configurations, and edge cases, without needing to collect real-world data for every scenario.