NVIDIA working with global robotics companies on physical AI

NVIDIA has announced it is partnering with the global robotics ecosystem to power production-scale physical AI. NVIDIA also unveiled new NVIDIA Isaac simulation frameworks and new NVIDIA Cosmos and NVIDIA Isaac GR00T open models for the industry to develop, train and deploy the next generation of intelligent robots.

Industry leaders building on the NVIDIA platform include ABB Robotics, AGIBOT, Agility, FANUC, Figure, Hexagon Robotics, KUKA, Skild AI, Universal Robots, World Labs and YASKAWA.

“Physical AI has arrived — every industrial company will become a robotics company,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA’s full-stack platform — spanning computing, open models and software frameworks — is the foundation for the robotics industry, uniting a worldwide ecosystem to build the intelligent machines that will power the next generation of factories, logistics, transportation and infrastructure.”

As industrial robotics becomes more AI driven, manufacturers need physically accurate, high-fidelity simulation to design, test and optimise systems before deployment.

With a global install base exceeding 2 million robots, FANUC, ABB Robotics, YASKAWA and KUKA are integrating NVIDIA Omniverse libraries and NVIDIA Isaac simulation frameworks into their virtual commissioning solutions to develop and validate complex robot applications and entire production lines through physically accurate digital twins. To power advanced intelligence on the production line, the companies are integrating NVIDIA Jetson modules into their controllers for real-time AI inference at the edge.

NVIDIA has also announced work with various companies to build generalised robot ‘brains’, to power the next generation of humanoid robots, and expanding physical AI to healthcare robotics.

NVIDIA says that by building an open and integrated platform for designing, training, testing and deploying physical AI, it is fostering collaboration in the robotics ecosystem, essential to scale deployments in the real world.

Image credit: iStock.com/Warut1