AWS offers accelerated robotics simulation with NVIDIA

NVIDIA Corp. today announced at AWS re:Invent enhanced tools for robotics developers, as well as the availability of NVIDIA DGX Cloud on Amazon Web Services and offerings for artificial intelligence and quantum computing.

The company said that NVIDIA Isaac Sim is now available on NVIDIA L40S graphics processing units (GPUs) in Amazon Elastic Cloud Computing (EC2) G6e instances. It said this could double scaling robotics simulation and accelerate AI model training. Isaac Sim is a reference application built on NVIDIA Omniverse for developers to simulate and test AI-driven robots in physically based virtual environments.

With NVIDIA OSMO, a cloud-native orchestration platform, developers can easily manage their complex robotics workflows across their AWS computing infrastructure, claimed the company.

“This combination of NVIDIA-accelerated hardware and software — available on the cloud — allows teams of any size to scale their physical AI workflows,” wrote Akhil Docca, senior product marketing manager for Omniverse at NVIDIA.

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What is ‘physical AI?’

According to NVIDIA, “physical AI” describes AI models that can understand and interact with the physical world. The company said it “embodies the next wave of autonomous machines,” such as self-driving cars, industrial manipulators, mobile robots, humanoids, and even robot-run infrastructure like factories and warehouses.

With physical AI, developers are embracing a “three-computer solution” for training, simulation, and inference to make breakthroughs, NVIDIA said. Yet physical AI for robotics systems requires robust training datasets to achieve precision inference in deployment. Developing such datasets and testing them in real situations can be impractical and costly.

Simulation offers an answer, as it can accelerate the training, testing and deployment of AI-driven robots, the company asserted.

L40S GPUs in the cloud offer to scale simulation, training

Developers can use simulation to verify, validate, and optimize robot designs as well as the systems and their algorithms before deployment, said NVIDIA. It added that simulation can optimize facility and system designs before construction or remodeling starts for maximum efficiencies, reducing costly manufacturing change orders.

Amazon EC2 G6e instances accelerated by NVIDIA L40S GPUs can double performance over the prior architecture, while allowing the flexibility to scale as scene and simulation complexity grows, NVIDIA said. Roboticists can use these instances to train many computer vision models that power AI-driven robots.

This means the same instances can be extended for various tasks, from data generation and simulation to model training. NVIDIA added that OSMO allows teams to orchestrate and scale complex robotics development workflows across distributed computing resources, whether on premises or in the AWS cloud.

NVIDIA said Isaac Sim can foster collaboration and critical workflows, such as generating synthetic data for perception model training.

A reference workflow combines NVIDIA Omniverse Replicator, a framework for building custom synthetic data generation (SDG) pipelines and a core extension of Isaac Sim, with NVIDIA NIM microservices. With it, developers can build generative AI-enabled SDG pipelines, it said.

These include the USD Code NIM microservice for generating Python USD code and answering OpenUSD queries, plus the USD Search NIM microservice for exploring OpenUSD assets using natural language or image inputs.

The Edify 360 HDRi NIM microservice can generate 360-degree environment maps, while the Edify 3D NIM microservice can create ready-to-edit 3D assets from text or image prompts. Generative AI can thus ease the synthetic data generation process by reducing many tedious and manual steps, from asset creation to image augmentation, said NVIDIA.

• Rendered.ai’s synthetic data engineering platform is integrated with Omniverse Replicator. It enables companies to generate synthetic data for computer vision models used in industries from security and intelligence to manufacturing and agriculture.
• SoftServe Inc., an IT consulting and digital services provider, uses Isaac Sim to generate synthetic data and validate robots used in vertical farming with Pfeifer & Langen, a leading European food producer.
• Tata Consultancy Services is building custom synthetic data generation pipelines to power its Mobility AI suite to address automotive and autonomous use cases by simulating real-world scenarios. Its applications include defect detection, end-of-line quality inspection, and hazard avoidance.

NVIDIA, AWS help robots learn in simulation

While Isaac Sim enables developers to test and validate robots in physically accurate simulation, Isaac Lab, an open-source robot learning framework built on Isaac Sim, provides a virtual playground for building robot policies that can run on AWS Batch. Because these simulations are repeatable, developers can troubleshoot and reduce the number of cycles required for validation and testing, said NVIDIA.

The company cited robotics startups that are already using Isaac Sim on AWS: 

• Field AI robot foundation models to enable robots to autonomously manage a wide range of industrial processes. It uses Isaac Sim and Isaac Lab to evaluate the performance of these models in complex, unstructured environments in construction, manufacturing, oil and gas, mining, and more.
• Vention, which offers a full-stack cloud-based automation platform, is creating pretrained skills to ease development of robotic tasks, noted NVIDIA. It is using Isaac Sim to develop and test new capabilities for robot cells used by small to midsize manufacturers.
• Cobot offers Proxie, its AI-powered collaborative mobile manipulator. It uses Isaac Sim to enable the robot to adapt to dynamic environments, work alongside people, and streamline logistics in warehouses, hospitals, airports, and more.
• Standard Bots is simulating and validating the performance of its R01 robot used in manufacturing and machining setup.
• Swiss-Mile is using Isaac Sim and Isaac Lab for robot learning so that its wheeled quadruped robots can perform tasks autonomously with new levels of efficiency in factories and warehouses.
• Cohesive Robotics has integrated Isaac Sim into its software framework called Argus OS for developing and deploying robotic workcells used in high-mix manufacturing environments.
• Aescape’s robots are able to provide precision-tailored massages by accurately modeling and tuning the onboard sensors in Isaac Sim.

NVIDIA made other announcements in addition to the availability of Isaac Sim 4.2 on Amazon EC2 G6e Instances powered by NVIDIA L40S GPUs on AWS Marketplace.

It said that NVIDIA DGX Cloud can run on AWS for training AI models; that AWS liquid cooling is available for data centers using its Blackwell platform; and that NVIDIA BioNeMo NIM microservices and AI Blueprints, developed to advance drug discovery, are now integrated into AWS HealthOmics.

The company also said its latest AI Blueprints are available on AWS for video search and cybersecurity, the integration of NVIDIA CUDA-Q with Amazon Braket for quantum computing development, and RAPIDS Quick Start Notebooks on Amazon EMR.

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