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NVIDIA Omniverse is the foundation for NVIDIA’s simulators, including the Isaac platform—which now includes several new features. Discover the next level in simulation capabilities for robots with NVIDIA Isaac Sim open beta, available now.
Built on the Omniverse platform, Isaac Sim is a robotics simulation application and synthetic data generation tool. It allows roboticists to train and test their robots more efficiently by providing a realistic simulation of the robot interacting with environments that can expand coverage beyond what is possible in the real world, NVIDIA reports.
This release of Isaac Sim also adds improved multi-camera support and sensor capabilities, and a PTC OnShape CAD importer to make it easier to bring in 3D assets. These new features will expand the breadth of robots and environments that can be successfully modeled and deployed in every aspect: from design and development of the physical robot, then training the robot, to deploying in a “digital twin” in which the robot is simulated and tested in an accurate and photorealistic virtual environment.
To deliver realistic robotics simulations, Isaac Sim leverages the Omniverse platform’s technologies including advanced GPU-enabled physics simulation with PhysX 5, photorealism with real-time ray and path tracing, and Material Definition Language (MDL) support for physically-based rendering.
Isaac Sim is built to address many of the most common robotics use cases including manipulation, autonomous navigation and synthetic data generation for training data. Its modular design allows users to easily customize and extend the toolset to accommodate many applications and and environments.
Isaac Sim benefits from Omniverse Nucleus and Omniverse Connectors, enabling collaborative building, sharing and importing of environments and robot models in Universal Scene Description (USD). Easily connect the robot’s brain to a virtual world through Isaac SDK and ROS/ROS2 interface, fully-featured Python scripting, plugins for importing robot and environment models.
Synthetic Data Generation is a tool that is used to train the perception models found in today’s robots. Isaac Sim has built-in support for a variety of sensor types that are important in training perception models. These sensors include RGB, depth, bounding boxes and segmentation.
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Sources: Press materials received from the company and additional information gleaned from the company’s website.


Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and…
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