{"id":78290,"date":"2026-06-05T16:31:09","date_gmt":"2026-06-05T16:31:09","guid":{"rendered":"https:\/\/www.europesays.com\/ch\/78290\/"},"modified":"2026-06-05T16:31:09","modified_gmt":"2026-06-05T16:31:09","slug":"delivering-industrial-grade-physical-ai-at-scale","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ch\/78290\/","title":{"rendered":"Delivering Industrial-Grade Physical AI at Scale"},"content":{"rendered":"<p>  <a id=\"startOfPage\"\/> <img decoding=\"async\" src=\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/06\/MD-0626-p11_fig1.jpg\" class=\" w-100 cld-responsive\" alt=\"\"\/> (From left to right) ABB Robotics RobotStudio\u00ae simulation compared to new RobotStudio\u00ae HyperReality, and a real-world image of the same robotic cell in a factory. (Image: ABB) <\/p>\n<p>ABB Robotics is integrating NVIDIA Omniverse libraries into ABB Robotics\u2019 RobotStudio \u00ae  to help manufacturers deploy physical AI in real-world robotics applications.<\/p>\n<p>\u201cUsing NVIDIA accelerated computing and simulation technologies, we have removed the last barriers to making industrial and physical AI a reality at a global scale by closing the sim-to-real gap,\u201d said Marc Segura, President of ABB Robotics.<\/p>\n<p>The collaboration focuses on combining ABB Robotics\u2019 software programming, design and simulation suite, RobotStudio, with the physically accurate simulation power of NVIDIA Omniverse libraries to close technology\u2019s long-standing \u2018sim-to-real\u2019 gap. Developers can simulate robots in digital twins and generate synthetic data to train their physical AI models, enabling businesses of all types and sizes to deploy AI-driven robotics for various industrial workflows.<\/p>\n<p> <img decoding=\"async\" src=\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/06\/MD-0626-p11_fig2.jpg\" class=\" w-100 cld-responsive\" alt=\"\"\/> By incorporating NVIDIA\u2019s accelerated computing and simulation power ABB Robotics\u2019 RobotStudio\u00ae HyperReality can create huge volumes of hyper realistic, industrial-grade simulations on which robots can be trained. (Image: ABB) <\/p>\n<p>Called RobotStudio HyperReality, the resulting physically accurate simulations and foundation models are endlessly optimized with real-world data feedback continuously improving the system. These models can be used to train any number of ABB robots, anywhere in the world, with the reliability and accuracy demanded by industry.<\/p>\n<p>\u201cThe industrial sector needs physically accurate simulation to bridge the gap between virtual training and the real-world deployment of AI-driven robotics at scale,\u201d said Deepu Talla, Vice President of Robotics and Edge AI at NVIDIA. \u201cIntegrating NVIDIA Omniverse libraries into RobotStudio brings advanced simulation and accelerated computing to ABB Robotics\u2019 unique virtual controller technology, accelerating how manufacturers of all sizes bring complex products to market.\u201d<\/p>\n<p>The long-standing deficit between simulation accuracy and real-world lighting, materials, and environments is known as the \u2018sim-to-real\u2019 gap. For decades, this gap has limited the ability of manufacturers to design and develop advanced manufacturing processes in the virtual world.<\/p>\n<p>By integrating Omniverse libraries into RobotStudio, ABB Robotics will deliver robotics simulation and synthetic data generation capabilities that will allow intelligent robots to bridge this gap with up to 99 percent accuracy. ABB has a virtual controller running the same firmware as the hardware, ensuring correlation between simulation and real world performance. Combined with ABB Robotics\u2019 Absolute Accuracy technology, which reduces positioning errors from 8\u201315 mm to around 0.5 mm, ABB delivers precision in both virtual and physical environments, making it suited to high-precision industrial-grade applications.<\/p>\n<p> <img decoding=\"async\" src=\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/06\/MD-0626-p11_fig3.jpg\" class=\" w-100 cld-responsive\" alt=\"\"\/> These simulations take into account different lighting, textures, materials, colors, angles \u2014 everything a robot would encounter on a real factory floor. (Image: ABB)<\/p>\n<p>ABB Robotics is also assessing the potential to integrate the NVIDIA Jetson edge computing platform into its Omnicore controller to achieve real-time AI inference at the edge for its robot portfolio.<\/p>\n<p>RobotStudio HyperReality will serve industrial clients at any scale, across a breadth of industries and applications, with select customers already testing its capabilities ahead of a full release to ABB Robotics\u2019 60,000 RobotStudio customers worldwide in the second half of 2026.<\/p>\n<p> <img decoding=\"async\" src=\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/06\/MD-0626-p12_fig1.jpg\" class=\" w-100 cld-responsive\" alt=\"\"\/> Built on ABB Robotics\u2019 technology, California-based robotic workforce company, WORKR, trains its robots with synthetic data using NVIDIA Omniverse libraries, which are deployed without operators needing to know any programming. Real-world image (bottom right) versus simulation. (Image: ABB) <\/p>\n<p>Foxconn, the world\u2019s largest electronics contract manufacturer, is piloting the first joint use case in consumer electronics assembly. Automating the assembly of a tiny piece in consumer electronics is challenging, as multiple device variants require different production methods and the delicate metal structure requires precise pick-and-place and assembly control, as well as fine-tuned setup, often demanding additional debugging time and engineering resources.<\/p>\n<p>Using RobotStudio HyperReality, Foxconn\u2019s assembly robots are trained virtually, using synthetic data to perfect multiple real-world production processes in various scenarios, before moving them to the production line with 99 percent accuracy. By optimizing production lines virtually, Foxconn will reduce set-up times and costs by eliminating physical training and tests, and accelerate time-to-market for consumer electronics.<\/p>\n<p>\u201cPrecision is everything in consumer electronics manufacturing and until now, this level of accuracy and fidelity just wasn\u2019t possible in simulation and digital twins,\u201d said Dr. Zhe Shi, Chief Digital Officer of Foxconn. \u201cWe\u2019re incredibly excited by the potential of ABB Robotics and NVIDIA\u2019s collaboration, which enables parallel engineering for better designs, faster production ramp-up, and greater product evolution through advanced AI inference and understanding.\u201d<\/p>\n<p>WORKR, a California-based robotic workforce company that delivers robotic manufacturing solutions to industry, is extending the reach of this technology to small and medium manufacturers across the U.S. At NVIDIA GTC 2026, WORKR demonstrated AI- powered robotic systems built on ABB technology, trained with synthetic data using NVIDIA Omniverse libraries, and deployed without operators needing to know any programming. By combining ABB\u2019s industrial grade robotics with its proprietary WorkrCore\u2122 AI platform, the company is helping manufacturers address critical labor shortages with its robotic workforce that can learn new tasks in minutes and be operated by anyone.<\/p>\n<p>\u201cThis collaboration is about making industrial AI deployable today,\u201d said Ken Macken, CEO &amp; Founder of WORKR. \u201cTogether with ABB and NVIDIA, we\u2019re proving that advanced automation can work for manufacturers of any size.\u201d<\/p>\n<p>This article was contributed by ABB (Cary, NC). For more information, visit  <a href=\"https:\/\/www.abb.com\/global\/en\/areas\/robotics\" target=\"_blank\" rel=\"noopener nofollow\">here\u00a0<\/a> . <\/p>\n<p>      More From SAE Media Group<br \/>\n   <img decoding=\"async\" src=\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/06\/MD-2026-06.jpg\" class=\"card-img-left lazyload blur-up\" width=\"400\" alt=\"Magazine cover\"\/>   Motion Design Magazine <\/p>\n<p class=\"card-text\">This article first appeared in the June, 2026 issue of Motion Design Magazine (Vol. 50 No. 6).<\/p>\n<p class=\"card-text\"> Read more articles from the archives <a href=\"https:\/\/www.techbriefs.com\/tb\/magazine\/archives\" rel=\"nofollow noopener\" target=\"_blank\">here<\/a>.<\/p>\n<p class=\"card-text\"><a href=\"https:\/\/tbm.dragonforms.com\/loading.do?omedasite=TEBland\" rel=\"nofollow noopener\" target=\"_blank\">  SUBSCRIBE  <\/a><\/p>\n<p>   var 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