What Is SimReady?

SimReady asset creation involves capturing the geometry, appearance, and real-world physical behaviors of objects, then structuring this digital representation to include all necessary simulation inputs. The standardized SimReady specification workflow guides developers to include attributes such as mass, friction, articulations, and semantic labels that bridge the gap between virtual and real applications.

SimReady Assets include features that enable robust interaction in synthetic environments, such as:

• Collision Shapes
  Define physical boundaries that determine how objects interact and collide within the simulation environment.
• Mass Properties
  Include weight, center of mass, and inertia data that enable realistic physics calculations during simulation.
• Material Details
  Specify surface characteristics like friction, elasticity, and visual properties that affect object behavior and appearance.

Developers can compose, configure, and deploy SimReady assets in various simulation scenarios—including industrial automation and robotics. Once validated, SimReady assets can also serve as ground-truth models for training AI agents in robotics, autonomous vehicle perception, and warehouse optimization.

To optimize the design, simulation, deployment and operations of AI factories, SimReady assets can be used to populate a digital twin of the AI factory with 3D models of power, cooling and mechanical systems.

SimReady assets enable AI and robotics training by providing labeled virtual data that replicates real-world complexity without real-world risks. Digital twins and photorealistic environments support training, testing, and validation of AI systems at scale, accelerating iteration and experimentation.

Asset behavior (such as sensor simulation) can be configured to represent a rich set of simulation scenarios to support reinforcement learning, supervised learning, and synthetic data generation for robotics and autonomous systems.

Once models are adequately trained in simulation, their knowledge and policies can be transferred to physical robots or systems for further real-world improvement.

By using SimReady assets, developers can design frameworks and benchmarks where robot performance is controlled and repeatable.

SimReady development standardization creates the foundation for simulation-ready 3D assets, enabling interoperable digital content for digital twins, robotics, and AI training. This evolving framework ensures virtual assets are not only visually accurate but also functionally consistent through three key principles:

• Feature Scaling: Expanding the capabilities of SimReady assets by incorporating more sophisticated features—like advanced physics behaviors and articulated parts—to support complex and realistic simulations.
• Pipeline Scaling: Automating the conversion of a high volume of source assets into a SimReady OpenUSD to enable efficient production for large-scale digital environments and training datasets.
• Standardization Review: Defining how SimReady features are represented within OpenUSD to ensure they're universally supported across the ecosystem, seamlessly scaling the number of compatible tools and platforms.

• Real-world accuracy: SimReady assets are photoreal and physically accurate to reflect real-world behavior in simulated environments, such as digital twins.
• Flexibility and Modularity: SimReady assets take advantage of the modular and flexible nature of USD, enabling developers to integrate 3D assets into any workflow or virtual world.
• Consistency: 3D developers working on digital twins have consistency across their asset libraries and can quickly build virtual worlds.
• Scalability: SimReady assets enable large-scale virtual training and testing, accelerating physical AI development across robotics, manufacturing, and other industries.

Manufacturing and Robotics

Building realistic factory simulations requires thousands of 3D assets. SimReady accelerates the development, testing, and management of AI-driven robots by providing photorealistic, physics-based assets.

Transportation and Logistics

SimReady assets, such as forklifts, racks, and conveyor belts, enable simulation of workflows, resource movement, and human-robot collaboration, allowing teams to optimize warehouse layout, train intelligent robot assistants, and boost productivity before real-world deployment.

Healthcare and Smart Spaces

Digital twins of hospitals, retail spaces, and urban infrastructure can improve safety analysis, process management, and efficiency planning. SimReady provides realistic assets to model and test these complex environments.

Autonomous Vehicles

Training autonomous systems requires highly realistic, varied environments. SimReady provides labeled, photorealistic street objects, vehicles, pedestrians, and hazards, accelerating sensor validation and AI model training.

SimReady standardization faces key challenges in a rapidly evolving technological landscape. The following must be addressed to ensure the framework’s long-term viability:

• Evolving Scope with Technology

  Rapid technological change makes it difficult to define an appropriate and enduring scope for SimReady features and pipeline workflows.

• Domain-Specific Needs

  Different industries have distinct requirements, priorities, and unit conventions. Ongoing standardization demands broad cross-industry collaboration to reduce ambiguity and ensure relevance.

• Integration Across Simulation Runtimes

  Maintaining compatibility across diverse simulation frameworks and tools, as well as downstream applications becomes more complex as domains and toolchains continue to evolve.

The SimReady standardization workflow helps to mitigate these challenges. This collaborative, phased process ensures the continuous iteration and refinement of standards, keeping the framework relevant and adaptable to future technological advancements and industry needs, as detailed in the documentation.

To get started, leverage the tools, standards, and resources below to begin using and creating SimReady assets.

• Explore assets in Isaac Sim: Start by downloading assets from NVIDIA’s physical AI dataset or Lightwheel’s extensive library, then try them out within NVIDIA Isaac Sim.
• Review the standardization workflow: Learn how to define and implement asset capabilities for your simulation projects using the SimReady standardization workflow.
• Get OpenUSD certified: Validate your expertise in building 3D content pipelines by earning the NVIDIA-Certified Professional OpenUSD Development certification.
• Contribute to the ecosystem: Use your domain expertise to contribute to the ongoing development of OpenUSD and SimReady standards through the Alliance for OpenUSD (AOUSD).