Siemens, Foxconn Fii, Wistron, and Caterpillar are among the companies using NVIDIA Omniverse to build digital twins of their factories. | Source: NVIDIA
NVIDIA Corp. this week gave a look at how leading manufacturers, industrial software developers, and robotics companies are using Omniverse technologies to build robotic factories and collaborative robotics. These systems will enable these companies to overcome labor shortages and drive American reindustrialization, NVIDIA said.
“AI is transforming the world’s factories into intelligent thinking machines — the engines of a new industrial revolution,” said Jensen Huang, founder and CEO of NVIDIA. “Together with America’s manufacturing leaders, we’re building physical AI, Omniverse digital twins, and collaborative robots that will drive productivity, resilience, and competitiveness across the U.S. industrial base.”
The robotics news was among the company‘s announcements at GTC (GPU Technology Conference) D.C. event. These included NVIDIA partnering with Uber to deploy autonomous vehicles in 2027 and releasing its new Blackwell-powered IGX Thor robotics processor.
The company said it built the IGX Thor platform to bring real-time physical AI directly to the edge, combining high-speed sensor processing, enterprise-grade reliability, and functional safety in a small module for the desktop.
Companies such as Diligent Robotics, EndoQuest Robotics, Hitachi Rail, Joby Aviation, Maven, and SETI Institute have already adopted IGX Thor.
Siemens, FANUC, and Foxconn are Omniverse Blueprint users
NVIDIA is expanding its Mega NVIDIA Omniverse Blueprint for simulating robot fleets to include technologies for designing factory digital twins. It said Siemens is the first company to develop digital twin software that supports the Mega Omniverse Blueprint.
Currently in beta testing, the new industrial technology stack will be part of the Siemens Xcelerator platform. It will help engineers design and operate large-scale digital twins of factories that bring together realistic 3D models with live operational data.
“Built for the AI era, this technology stack enables comprehensive simulation, optimization, and real-time performance monitoring that can help design smarter and more efficient factories, products, and data centers,” asserted NVIDIA.
FANUC and Foxconn Fii are among the first robot vendors to support 3D, OpenUSD-based digital twins of their robots to make it easy for manufacturers to drag and drop equipment into their digital twins.
In his GTC keynote in Washington, D.C., Huang showcased how Foxconn is using the new Omniverse technologies to design, simulate, and optimize its new 242,287 sq. ft. (22,509.1 sq. m) facility in Houston for manufacturing NVIDIA AI infrastructure systems.
Leading companies use Omniverse to build robotic factories
NVIDIA said leading U.S. businesses are relying on applications from independent software vendors and Omniverse libraries to build robotic factories. It added that these could enable a new wave industrialization and reshoring, using physical AI and simulation to accelerate manufacturing.
Belden has implemented Accenture’s Physical AI Orchestrator, which combines NVIDIA Omniverse libraries, the NVIDIA Metropolis platform, and agentic AI from Accenture, to create virtual safety fences for instant hazardous zone monitoring and real-time quality-inspection systems in factories and warehouses.
Caterpillar is applying Omniverse to build digital twins of its factories and supply chains, for use in advanced manufacturing capabilities. This includes predictive maintenance and dynamic scheduling, NVIDIA NIM microservices to drive workflow automation and predict and optimize factory maintenance, and NVIDIA cuOpt software to optimize supply chain performance.
Lucid Motors is using Omniverse to build digital twins of its factories for real-time factory planning and optimization, as well as to train AI-driven robotics systems.
Toyota is using idealworks’ iw.sim technology, which integrates capabilities from the Mega Omniverse Blueprint, to create digital twins of its facility in Georgetown, Ky., and to explore complex automation scenarios.
TSMC is using Omniverse to accelerate chip fab design and construction, as well as the NVIDIA Isaac platform for the development of robotics for specific operations at its factory in Phoenix, Ariz., to significantly enhance productivity.
Wistron is using a suite of NVIDIA AI and Omniverse technologies to implement a rigorous digital testing and validation process for the electronics it assembles in Fort Worth, Texas.
Assembling a robotic workforce with NVIDIA
Robotics companies are using NVIDIA’s three-computer architecture to build and deploy advanced fleets of robots that will play a critical role in bridging skills gaps, enhancing worker productivity, and improving safety across industries.
Figure and NVIDIA announced a collaboration to accelerate next‑generation humanoid robotics. Using NVIDIA accelerated computing to build its Helix vision language action model and the Isaac platform for simulation and training, Figure is rapidly building the world’s most advanced, large‑scale humanoid fleet capable of everything from household chores to industrial support.
Agility Robotics’ general-purpose humanoid, Digit, uses the NVIDIA Isaac Lab framework to refine whole-body control through millions of reinforcement learning scenarios, which accelerate enhancements to its skillsets, such as step recovery from environmental disturbances, often needed in highly dynamic areas like manufacturing and logistics facilities. Digit is powered by the NVIDIA Jetson AGX Thor module, enabling real-time perception, navigation, and autonomous decision-making.
Amazon Robotics is using Omniverse libraries and frameworks to shorten the development of Amazon’s various manipulation systems and mobile robots, which run on the NVIDIA Jetson platform, from years to months. Thanks to simulation training, Amazon’s recently announced BlueJay multi-arm manipulator for picking, stowing, and consolidating moved from concept to production in just over a year.
Skild AI is building a general-purpose robotics foundation model that spans legged, wheeled, and humanoid robots, using Isaac Lab for locomotion and dexterous manipulation tasks training, and NVIDIA Cosmos world foundation models for generating training datasets.
FieldAI is training cross-embodied robot brains for monitoring and inspection in construction and oil and gas environments, using Isaac Lab for reinforcement learning and NVIDIA Isaac Sim for synthetic data generation and software-in-the-loop validation.
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