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Everything that moves will one day be autonomous. Today, demand for autonomous machines and AI-enabled robots is at an all-time high, as industries look to improve operational efficiency, combat workforce shortages, optimize repetitive tasks, and manage dangerous tasks or environments.
With NVIDIA’s three-computer solution, AI robots can adapt, learn, and perform complex tasks with precision. This is made possible by advancements in AI, accelerated computing, physically based simulation, and a vast ecosystem of sensors and actuators.
Developers are taking advantage of NVIDIA Robotics’ full-stack, accelerated cloud-to-edge systems, acceleration libraries, and optimized AI models to develop, train, simulate, deploy, operate, and optimize their robot systems and software like never before.
NVIDIA Isaac GR00T N1 brings generalized skills and reasoning to humanoid robots.
New NVIDIA Isaac for Healthcare Medical Device Simulation Platform to Fast-Track Development of Autonomous Imaging Systems and Robotics
Accelerate the development of advanced AI robotics.
General-purpose humanoid robots are designed to quickly adapt to human-centric urban and industrial workspaces, tackling tedious, repetitive, or physically demanding tasks. They’re increasingly being used in factories and healthcare facilities to assist humans and alleviate labor shortages through automation.
Train robot policies in simulation.
Preprogrammed robots struggle with unexpected changes, while AI-driven robots use simulation-based learning to adapt to dynamic environments. This lets them refine capabilities like navigation and manipulation, improving performance in a wide variety of scenarios.
Develop physically accurate sensor simulation pipelines for robotics.
Physical AI-powered robots need to autonomously perform complex tasks in dynamic environments. A "sim-first" approach is essential, allowing developers to train and validate these robots in physics-based digital environments before deployment.
Use this robot learning technique to develop adaptable and efficient robotic applications.
As robots tackle more complex tasks, traditional programming falls short. Reinforcement learning (RL) addresses this gap by training robots in virtual environments through trial and error—improving their skills in control, path planning, and manipulation.
Develop advanced, generative AI-enabled virtual facility solutions.
Virtual facilities—including factories, warehouses, distribution centers, semiconductor fabs, and data centers—unlock new possibilities for heavy industries. These virtual environments enable the design, simulation, operation, and optimization of assets and processes entirely in a digital space.
DGX Spark brings the power of NVIDIA Grace Blackwell™ to developer desktops. The GB10 Superchip, combined with 128 GB of unified system memory, lets AI researchers, data scientists, and students work with AI models locally with up to 200 billion parameters.
Learn about the NVIDIA Robotics platform for robotics and vision AI.
The NVIDIA Isaac™ robotics platform includes a full suite of NVIDIA® CUDA®-accelerated systems, libraries, application frameworks, and generative AI models. These help you advance AI perception, manipulation, and simulation.
NVIDIA Metropolis is an application framework, set of developer tools, and partner ecosystem that brings together visual data and AI. This helps improve operational efficiency and safety across a range of industries.
Physically accurate simulation and synthetic data generation accelerate the development, testing, and validation of AI robots. NVIDIA Isaac Sim is a fully customizable application framework, built on Omniverse,™ that lets you use these tools to simulate and test your AI robots’ trained skills.
AI robot development workflows are complex, requiring many workloads to be orchestrated across several compute environments. Now, developers can use NVIDIA OSMO to easily deploy multi-container workloads across heterogeneous shared compute resources with no specialized knowledge.
NVIDIA Isaac ROS is built on the open-source ROS 2™ (Robot Operating System) software framework. This means the millions of developers in the ROS community can easily take advantage of NVIDIA-accelerated libraries and AI models to accelerate their AI robot development and deployment workflows.
Discover a large community of partners that can help you build your full robot system with products ranging from specialized boards to AI software to application design services to sensors and developer tools.
Physical AI models can perceive, understand, interact, and navigate the physical world using generative AI.
NVIDIA unveiled a suite of services, models, and computing platforms designed to accelerate the development of humanoid robots globally.
See how NVIDIA has evolved from creating advanced autonomous vehicle hardware and simulation tools to developing cutting-edge AI for humanoid robots.
Training humanoid robots to operate in fields that demand high levels of interaction and adaptability can be a challenging and resource-intensive feat.
Robotic dexterous grasping enables robots to handle complex tasks with fine motor skills, significantly boosting productivity and efficiency.
Programming robots for real-world success involves training them to handle unpredictable conditions and object variations. Accurate simulations are crucial for this training.
Connect with millions of like-minded developers and access hundreds of GPU-accelerated containers, models, and SDKs—all the tools necessary to successfully build apps with NVIDIA technology—through the NVIDIA Developer Program.
Evolve your startup with go-to-market support, technical expertise, training, and funding opportunities.
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