NVIDIA announced it is providing the world’s leading robot manufacturers, AI model developers and software makers with a suite of services, models and computing platforms to develop, train and build the next generation of humanoid robotics.
Among the offerings are new NVIDIA NIM™ microservices and frameworks for robot simulation and learning, the NVIDIA OSMO orchestration service for running multi-stage robotics workloads, and an AI- and simulation-enabled teleoperation workflow that allows developers to train robots using small amounts of human demonstration data.
“The next wave of AI is robotics and one of the most exciting developments is humanoid robots,” said Jensen Huang, founder and CEO of NVIDIA. “We’re advancing the entire NVIDIA robotics stack, opening access for worldwide humanoid developers and companies to use the platforms, acceleration libraries and AI models best suited for their needs.”
Accelerating Development With NVIDIA NIM and OSMO
NIM microservices provide pre-built containers, powered by NVIDIA inference software, that enable developers to reduce deployment times from weeks to minutes. Two new AI microservices will allow roboticists to enhance simulation workflows for generative physical AI in NVIDIA Isaac Sim™, a reference application for robotics simulation built on the NVIDIA Omniverse™ platform.
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The MimicGen NIM microservice generates synthetic motion data based on recorded teleoperated data from spatial computing devices like Apple Vision Pro. The Robocasa NIM microservice generates robot tasks and simulation-ready environments in OpenUSD, a universal framework for developing and collaborating within 3D worlds.
NVIDIA OSMO, available now, is a cloud-native managed service that allows users to orchestrate and scale complex robotics development workflows across distributed computing resources, whether on premises or in the cloud.
OSMO vastly simplifies robot training and simulation workflows, cutting deployment and development cycle times from months to under a week. Users can visualize and manage a range of tasks — like generating synthetic data, training models, conducting reinforcement learning and implementing software-in-the-loop testing at scale for humanoids, autonomous mobile robots and industrial manipulators.
Advancing Data Capture Workflows for Humanoid Robot Developers
Training foundation models for humanoid robots requires an incredible amount of data. One way of capturing human demonstration data is using teleoperation, but this is becoming an increasingly expensive and lengthy process.
An NVIDIA AI- and Omniverse-enabled teleoperation reference workflow, demonstrated at the SIGGRAPH computer graphics conference, allows researchers and AI developers to generate massive amounts of synthetic motion and perception data from a minimal amount of remotely captured human demonstrations.
First, developers use Apple Vision Pro to capture a small number of teleoperated demonstrations. Then, they simulate the recordings in NVIDIA Isaac Sim and use the MimicGen NIM microservice to generate synthetic datasets from the recordings.
SOURCE: GlobeNewswire
