ABB and NVIDIA: Physical AI Transforms Automation

The partnership between ABB and NVIDIA marks a significant advancement in industrial automation through the integration of physical AI. This partnership aims to address a persistent issue for manufacturers: the gap between digital simulations and real-world conditions on production lines. Differences in lighting, material physics, and part variations often render intelligent robots unreliable outside of test environments.

Historically, this disparity has forced engineers to revert to physical prototypes, delaying product launches and increasing costs. To overcome these obstacles, ABB Robotics and NVIDIA have joined forces to introduce industrial-level physical AI into manufacturing facilities.

RobotStudio HyperReality: An Anticipated Revolution

Set to launch in the second half of 2026, the RobotStudio HyperReality software is already generating global interest. By integrating NVIDIA Omniverse libraries into its RobotStudio software, ABB offers a platform that enables digital testing with enhanced physical accuracy. This integration can reduce deployment costs by up to 40% and accelerate time-to-market by up to 50%.

To achieve these efficiency gains, production managers can design, test, and validate complete automation cells before installing hardware. The system exports a fully parameterized station, including robots, sensors, lighting, kinematics, and parts, in the form of a USD file within the Omniverse environment.

In this digital space, a virtual controller runs the same firmware as the physical machines, ensuring a 99% behavioral match between the digital and physical domains. Rather than manually programming movements, computer vision models learn using synthetic images generated within the software. This method, combined with Absolute Accuracy technology, reduces positioning errors from 8-15 mm to around 0.5 mm, providing high precision for industrial applications.

Marc Segura, President of ABB Robotics, stated: “By combining RobotStudio with the physically accurate simulation power of NVIDIA Omniverse libraries, we have bridged the long-standing gap between the 'sim-to-real' technology – a major step towards deploying physical AI with industrial-level precision for real applications at our customers.”

Field Validation by Industry Leaders

Early adopters are already validating these capabilities on active production lines. Foxconn, for example, is testing the software for assembling consumer devices, an area where frequent product changes and delicate metal components complicate traditional automation. By generating synthetic data to train their systems virtually, Foxconn achieves high precision on the ground while anticipating reduced setup time and the elimination of costly physical testing.

Similarly, Workr – a California-based automation provider – is integrating its WorkrCore platform with ABB hardware trained via Omniverse. At the NVIDIA GTC 2026 event in San Jose, Workr plans to showcase systems capable of integrating new parts in minutes without requiring specialized programming skills.

Deepu Talla, Vice President of Robotics and Edge AI at NVIDIA, commented: “The industrial sector needs high-fidelity simulations to bridge the gap between virtual training and the real-world deployment of AI-powered robots at scale. The integration of NVIDIA Omniverse libraries into RobotStudio brings advanced simulation and accelerated computing to ABB's virtual controller technology, speeding up how thousands of manufacturers bring complex products to market.”

The hardware ecosystem is also expanding to edge computing. ABB is evaluating the integration of the NVIDIA Jetson platform into its Omnicore controllers, a step that would facilitate real-time inference across existing robotic fleets. Adopting this type of digital simulation for physical AI can reduce setup and commissioning times by up to 80%. As AI transitions from software applications to hardware operations, preparing data pipelines and refining engineering teams to work with synthetic data will determine which manufacturers maintain a competitive edge.