As robots increasingly undertake complex mobility tasks, developers require accurate simulations that can be applied across various environments and workloads. Collecting high-quality data in the physical world is often costly and time-consuming, making synthetic data generation at scale essential for advancing physical AI. NVIDIA Isaac Sim and NVIDIA OSMO provide a comprehensive solution for building simulated environments and orchestrating end-to-end synthetic data generation workflows. These tools allow developers to create physics-accurate simulations, generate diverse datasets using MobilityGen, and enhance data with visual diversity through Cosmos Transfer. By leveraging cloud technology and open-source frameworks, developers can efficiently train robot policies and models, bridging the gap between simulated and real-world data. This matters because it accelerates the development and deployment of advanced robotics systems, making them more adaptable and efficient in real-world applications.
Creating realistic 3D environments for robotics simulation has become significantly more efficient with the integration of NVIDIA Isaac Sim and World Labs Marble. By utilizing generative world models, developers can rapidly transform text or image prompts into photorealistic, simulation-ready worlds, drastically reducing the time and effort traditionally required. This process involves exporting scenes from Marble, converting them to compatible formats using NVIDIA Omniverse NuRec, and importing them into Isaac Sim for simulation. This streamlined workflow enables faster robot training and testing, enhancing the scalability and effectiveness of robotic development. This matters because it accelerates the development and testing of robots, allowing for more rapid innovation and deployment in real-world applications.