Nvidia and Hugging Face to Advance Open-Source AI Robotics Research and Development

Collaboration between Hugging Face and Nvidia integrates AI and robotics with high-fidelity simulation tools, enhancing industries from healthcare to logistics.

Highlights

  • Hugging Face and Nvidia team up at CoRL to drive AI robotics research.
  • Integration of Hugging Face’s LeRobot with Nvidia’s Omniverse and Isaac Lab.
  • Focus on physical AI, facilitating robotics training and real-world applications.

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Nvidia and Hugging Face to Advance Open-Source AI Robotics Research and Development
Hugging Face and Nvidia announced a collaboration to accelerate open-source AI robotics research and development at the Conference for Robot Learning (CoRL) in Munich. The partnership combines Hugging Face's LeRobot open AI platform with Nvidia's simulation tools, including Omniverse and Isaac robotic technology, to enable researchers and developers to drive progress across a range of industries, including manufacturing, healthcare and logistics.

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Hugging Face and Nvidia

The collaboration focuses on the field of physical AI, where robots learn to understand and interact with the physical world. By integrating Hugging Face's open-source resources, such as its model hub, with Nvidia's high-fidelity simulation capabilities, the initiative aims to streamline robot training, data collection, and deployment.

According to the official release, Hugging Face's open AI platform serves over 5 million machine learning researchers and developers, offering tools and resources to streamline AI development. The LeRobot platform extends Hugging Face's AI expertise into robotics, offering tools for data sharing, model training, and simulation, alongside designs for low-cost manipulator kits.

Nvidia's Isaac Lab enhances these capabilities by providing scalable simulation environments to generate vast amounts of training data, accelerating the development process.

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Powering AI Development in Robotics

The partnership also promotes a collaborative ecosystem by enabling the sharing of datasets, policies, and models within the Hugging Face community, creating a "data flywheel" effect that allows researchers to build on each other's work and fast-track AI-powered robotics, the official release said.

"The robotics community thrives when we build together," said Animesh Garg, assistant professor at Georgia Tech. "By embracing open-source frameworks such as Hugging Face's LeRobot and Nvidia Isaac Lab, we accelerate the pace of research and innovation in AI-powered robotics."

"Combining Hugging Face open-source community with Nvidia's hardware and Isaac Lab simulation has the potential to accelerate innovation in AI for robotics," said Remi Cadene, principal research scientist at LeRobot.

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With early demonstrations, such as a physical picking setup using LeRobot on Nvidia's Jetson Orin Nano, the collaboration aims to accelerate the work of robotics researchers and developers worldwide, transforming industries ranging from transportation to manufacturing and logistics, the companies said.

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