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NVIDIA has announced the launch of NVIDIA Omniverse Cloud Sensor RTX™, a suite of microservices designed to provide physically accurate sensor simulation, thereby accelerating the development of autonomous machines. This announcement was made at the Computer Vision and Pattern Recognition (CVPR) conference, according to the NVIDIA Newsroom. Revolutionizing Sensor Simulation The Omniverse Cloud Sensor RTX aims to revolutionize the sensor industry, which is a rapidly growing multibillion-dollar sector. These microservices enable developers to test sensor perception and related AI software extensively in realistic virtual environments before deploying them in the real world. This approach not only enhances safety but also reduces time and costs associated with physical prototyping. “Developing safe and reliable autonomous machines powered by generative physical AI requires training and testing in physically based virtual worlds,” said Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA. “NVIDIA Omniverse Cloud Sensor RTX microservices will enable developers to easily build large-scale digital twins of factories, cities, and even Earth — helping accelerate the next wave of AI.” Supercharging Simulation at Scale Built on the OpenUSD framework and powered by NVIDIA RTX™ ray-tracing and neural-rendering technologies, Omniverse Cloud Sensor RTX combines real-world data from various sources like videos, cameras, radar, and lidar with synthetic data to create highly accurate simulated environments. These capabilities are particularly useful in scenarios where real-world data is limited. The microservices can simulate a wide range of activities, such as checking if a robotic arm is functioning correctly, verifying an airport luggage carousel’s operation, detecting if a tree branch is obstructing a roadway, or ensuring that a factory conveyor belt is running smoothly. Research Milestones and Real-World Applications The announcement coincides with NVIDIA’s first-place win at the CVPR Autonomous Grand Challenge for End-to-End Driving at Scale. The winning workflow, which can be replicated using Omniverse…

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Filed under: News - @ June 18, 2024 12:26 pm