Physical AI—AI systems that perceive, reason, and act in physically grounded simulated environments—is changing how teams design and validate robots and…

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NVIDIA is introducing a modular, library-based architecture for Omniverse, exposing core capabilities—RTX rendering (ovrtx), PhysX simulation (ovphysx), and data storage (ovstorage)—as standalone C APIs with Python bindings. This allows developers to integrate physical AI capabilities into existing applications without adopting the full Omniverse container stack. Isaac Lab 3.0 Beta demonstrates the approach by transitioning from the monolithic Kit framework to a multi-backend architecture supporting pluggable physics (ovphysx or MuJoCo-Warp) and rendering backends. The libraries also support MCP servers for LLM-based agent orchestration, enabling tools like Claude and Cursor to interact with simulation environments. Industrial partners including ABB Robotics, Siemens, PTC, and Cadence are already adopting these libraries. All three libraries are currently in early access on GitHub and NGC, with production releases planned later in 2025.

Integrate Physical AI Capabilities into Existing Apps with NVIDIA Omniverse Libraries

Delivering value through modular simulation

Getting Started: Wiring physical AI into your pipeline