Ingyenes 3D-könyvtárat indított az Nvidia és a Hugging Face

Building robotics simulations and high-fidelity AI factory digital twins takes more than 3D models. Developers often need to add properties such as collision geometry, mass, and friction. SimReady assets are 3D models that come prepared with the properties required for simulation workflows, reducing that manual work. SimReady Central Library brings together more than 2,000 simulation-ready (SimReady) OpenUSD assets on Hugging Face, giving developers a free, ungated starting point for physical AI training environments and AI factory digital twins. The library includes a variety of infrastructure and equipment assets from robot arms and grippers to warehouse equipment, racks, and cooling infrastructure. Developers can check which capabilities each asset supports, then combine assets from different suppliers into a scene. Equipment manufacturers (OEMs) can now prepare and validate assets against SimReady requirements and use SimReady Central Library to reach developers and allow their end customers to test and simulate scenarios faster and accelerate decision making. This enables industries to build simulations around their products while managing their own Hugging Face datasets. We’ll cover what makes an asset SimReady and how OEMs contribute to SimReady Central Library, then show how developers can use those assets to build a robotic pick-and-place scenario and compare AI factory layouts. SimReady assets are OpenUSD assets prepared with the properties required for simulation workflows. A detailed 3D model, such as CAD, is a useful starting point. Simulation requires additional information about how that object should be interpreted and used. For a robot manipulation task, that might include the object’s mass, collision geometry, and friction properties. For AI factory workflows, it might include equipment geometry and the electrical or thermal metadata required by the application. OpenUSD is an open, extensible framework for describing and composing 3D scenes. Using those scenes to train and evaluate autonomous machines also requires information about physical behavior, collisions, and sensor interactions. SimReady Foundation provides specifications, profiles, and validation tools that make these requirements explicit. A profile defines the logical grouping of features and capabilities an asset needs for a particular use case. Figure 1. SimReady Foundation defines asset representation requirements for specific simulation use cases, while developer libraries help prepare and validate OpenUSD assets against those requirements. Depending on the asset and profile, those features can include: For the requirements associated with each simulation use case, see the SimReady Foundation requirements and profiles. Developers should select assets from SimReady Central whose profiles match their workflow needs and compose them into an OpenUSD scene. OEMs can turn their CAD equipment models into SimReady assets for developers building simulations around their products. SimReady Central Library makes those assets discoverable on Hugging Face, helping manufacturers reach teams building robotics simulations and AI factory digital twins. For AI factory OEMs like Vertiv, the library provides a path to distribute assets such as warehouse equipment racks, server racks, cooling equipment, and supporting infrastructure for AI factory digital twins. Developers and frontier agents can incorporate these assets into AI factory digital twins reusing the geometry and properties specified by their SimReady profiles. For robotics OEMs like Comau, FANUC, Franka Robotics, Robotiq, Standard Bots, and Universal Robots, the library makes robot arms and grippers discoverable by teams building training and evaluation environments. Developers can combine these assets with industrial equipment to build warehouse and factory scenarios. For simulation asset providers like Palatial the library features the NVIDIA Robotics 1K Dataset released in collaborati