NVIDIA Isaac Sim
7 use cases using this technology
How Bouygues Construction Drives Sustainable Building Innovation With Digital Twins
Bouygues Construction
Bouygues Construction, a global construction and infrastructure company based in France, built custom digital twin applications on NVIDIA Omniverse using the OpenUSD framework to unify 3D data from Revit, SolidWorks, and Cesium into a single collaborative environment. Using NVIDIA Isaac Sim, the company generates photorealistic synthetic training data for AI-based computer vision models covering rare or hazardous jobsite scenarios, and uses NVIDIA RTX PRO GPUs for real-time ray tracing. The approach delivered a 5x improvement in data integration speed and enabled safer job site planning through AI-driven construction site simulations and predictive scenario testing.
How Serve Robotics Achieved 99.8% Success for Last-Mile Autonomous Delivery
Serve Robotics
Serve Robotics, which spun off from Uber in 2021, operates over 1,000 physical AI-powered sidewalk delivery robots serving over 2,500 restaurants across five cities. Its third-generation robots are simulated in NVIDIA Isaac Sim and powered by NVIDIA Jetson Orin edge AI platforms, achieving a 5x compute improvement over the prior Xavier generation and 12+ hours of battery life. The fleet has completed over 100,000 autonomous deliveries with a 99.8% completion rate, logging about 1 million miles of data monthly (nearly 170 billion image-LiDAR samples) to improve navigation and HD maps. The company plans to deploy 2,000 robots by the end of 2025.
Lightwheel deploys NVIDIA GR00T N1.5 humanoid robots in Geely's live automotive factory using Isaac Sim simulation
Geely
Lightwheel built a simulation-first robotics platform on NVIDIA Isaac Sim, Isaac Lab, and NVIDIA Omniverse libraries to address data scarcity and the sim-to-real gap in physical AI development. For Geely, Lightwheel fine-tuned the NVIDIA Isaac GR00T N1.5 vision-language-action foundation model to the Unitree H1 humanoid robot's morphology using simulation-generated synthetic data and DexMimicGen data augmentation, then deployed it in Geely's live automotive factory where robots autonomously perform component transportation, precise part placement on inspection trays, and coordinated dual-arm manipulation for heavy components. The platform achieves a 100:1 simulated-to-real data ratio and reduced development cycles from months to weeks.
Foxconn Develops Physical AI-Enabled Smart Factories With Digital Twins
Foxconn (Hon Hai Technology Group)
Foxconn (Hon Hai Technology Group) uses physically accurate digital twins integrating NVIDIA Omniverse libraries and OpenUSD to design, deploy, and manage high-volume production facilities, including those producing NVIDIA GB200 Grace Blackwell Superchip systems. Its Fii Omniverse Digital Twin (FODT) platform creates virtual replicas of factories, enabling simulation-driven design, real-time monitoring, and optimized operations. Using NVIDIA PhysicsNeMo AI models, Foxconn achieves 150x faster computational fluid dynamics simulations for thermal analysis (minutes vs. hours). Standardized OpenUSD-based digital twin assets enable rapid migration of entire production lines between global factories (e.g., Taiwan to Mexico). Robot workcells and AGV logistics are simulated in FODT before physical deployment: complex robotic tasks such as screw tightening and cable insertion are simulated and refined with NVIDIA Isaac Sim, Isaac Lab, FoundationPose models, and NVIDIA cuMotion, while AGV path is optimized by connecting simulations with Material Control Systems and NVIDIA cuOpt. Foxconn also built video analytics AI agents with NVIDIA Metropolis and the NVIDIA AI Blueprint for video search and summarization to monitor factory floors, and developed FoxBrain, an AI platform powered by NVIDIA NeMo trained in four weeks, described as Taiwan's first large language model with advanced reasoning capabilities. Leo Guo, General Manager of Fii Robotic Group, said the company believes it can cut factory setup and planning time by about 50%.
Hyundai Motor Group builds NVIDIA Blackwell AI factory for mobility and smart factories
Hyundai Motor Group
Hyundai Motor Group is building an AI factory using 50,000 NVIDIA Blackwell GPUs to train, validate and deploy AI for in-vehicle systems, autonomous driving, smart factories and robotics. The collaboration includes an approximately $3 billion investment with the Korean government to build a national physical AI cluster, an NVIDIA AI Technology Center and Hyundai's Physical AI Application Center. Hyundai is exploring using NVIDIA Omniverse and Cosmos on RTX PRO Servers for factory digital twins, and using NVIDIA DRIVE AGX Thor running DriveOS for driver-assistance and in-vehicle AI.
BMW uses NVIDIA Omniverse Enterprise and Isaac Sim to build digital twins of its factories
BMW
BMW, which produces 2.5 million cars a year with 99 percent of them customized before purchase, uses NVIDIA Omniverse Enterprise to simulate its factories in real time as a photorealistic digital twin, connecting applications like Bentley Microstation and Autodesk Revit. BMW also employs NVIDIA Isaac Sim to train delivery robots using synthetic data generation with domain randomization, and NVIDIA Fleet Command to orchestrate robots and machines across its production network.
Robot Retasking in High-Mix Manufacturing with Workr
Workr
Workr, a manufacturing AI company, uses NVIDIA Omniverse, Isaac Sim and accelerated computing to let on-site operators retask industrial robots in under five minutes via a tablet interface, eliminating weeks of traditional programming. The edge AI pipeline runs on 2x NVIDIA RTX PRO 6000 Blackwell Max-Q GPUs attached to the robot cell, using models including RAFT-Stereo, Detectron2, NVIDIA Isaac FoundationPose and NVIDIA Isaac cuMotion, trained with synthetic data generated in Isaac Sim digital twins. Deployed with customers Yuasa International and Haas Alfex.