Combining AI foundation models, high-performance edge computing, simulation tools, and advanced robotic hardware, this new open reference design aims to simplify humanoid robot development and accelerate deployment across industries.
Humanoid robots are rapidly evolving from research concepts into practical machines capable of assisting in manufacturing, logistics, healthcare, and service industries. However, building a humanoid robot remains a highly complex task that requires expertise in artificial intelligence, mechanical design, sensing, motion control, and computing. To simplify development and accelerate innovation, NVIDIA has introduced an open humanoid robot reference design that combines advanced AI models, high-performance computing hardware, simulation tools, and robotic components into a unified platform. The initiative aims to provide developers with a ready-to-use foundation that can significantly reduce development time and enable faster deployment of intelligent humanoid systems.
At the heart of the reference design is NVIDIA Isaac GR00T, an open foundation model developed specifically for humanoid robots. Unlike conventional robots that rely heavily on predefined instructions, GR00T uses a Vision-Language-Action architecture that allows robots to understand natural language commands, interpret their surroundings, and generate appropriate actions. The model is based on a dual-system approach inspired by human cognition. One system handles fast, real-time motor actions and movement control, while the second focuses on reasoning, planning, and decision-making. This combination enables robots to perform complex tasks that require both intelligence and physical interaction with the environment.
The reference platform integrates NVIDIA’s Jetson Thor computing system, which delivers the processing power needed for perception, planning, and real-time control. The hardware architecture also includes the Unitree H2 Plus humanoid robot and Sharpa’s dexterous five-finger robotic hands. These advanced robotic hands provide the fine motor skills required for grasping, manipulating objects, handling tools, and performing delicate tasks. Together, the hardware and software components form a complete development ecosystem for creating next-generation humanoid robots.
A major challenge in robotics is training machines efficiently and safely. NVIDIA addresses this through its Isaac simulation platform, which allows developers to train robots in virtual environments before deploying them in the real world. Using simulation and synthetic data generation, robots can learn a wide variety of tasks without requiring extensive physical testing. This approach reduces development costs, shortens training time, and improves system reliability. Developers can generate large amounts of training data and evaluate robot performance under different scenarios before actual deployment.
The open reference design is expected to support a wide range of applications, including industrial automation, warehouse operations, healthcare assistance, and service robotics. By providing open access to AI models, development tools, datasets, and benchmarks, NVIDIA aims to create a collaborative ecosystem that encourages innovation across the robotics community. As advances in AI, simulation, and robotic hardware continue to converge, open platforms such as this could play a key role in accelerating the adoption of humanoid robots and bringing intelligent machines into everyday environments.
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