Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in OpenUSD , add physics properties, render preflight views, and validate the result against simulation-ready (SimReady) requirements. This workflow follows that process from a scene in Blender to a simulation-ready OpenUSD handoff for NVIDIA Isaac Sim or NVIDIA Isaac Lab .

In practice, however, if you’re building agents for robotics, the workflow can often get stuck. It’s tempting to blame the hard part on the policy, the model, or the training loop, but the bottleneck often happens earlier: the robot does not have a simulation-ready world to train in. The extra work required to get a 3D scene into that state is laborious, time consuming, and frequently out of scope for the robotics simulation engineer.

This post walks through an agent workflow for preparing a Blender scene for robotics simulation using NVIDIA Omniverse Libraries .…