As the manufacturing industry faces challenges - such as labor shortages, reshoring and inconsistent operational strategies - AI-powered robots present a significant opportunity to accelerate industrial automation.
At Automate, the largest robotics and automation event in North America, robotics leaders KUKA, Standard Bots, Universal Robots (UR) and Vention are showcasing hardware and robots powered by the NVIDIA accelerated computing, Omniverse and Isaac platforms - helping manufacturers everywhere automate and optimize their production lines.
Deepu Talla, vice president of robotics and edge AI at NVIDIA, delivered a keynote on physical AI and industrial autonomy.
The manufacturing industry is experiencing a fundamental shift, with industrial automation and AI-powered robots increasingly changing how warehouses and factories operate worldwide, said Deepu Talla, vice president of robotics and edge AI at NVIDIA. NVIDIA's three-computer architecture - enabling robot training, simulation and accelerated runtime - is empowering the entire robotics ecosystem to accelerate this shift toward software-defined autonomous facilities.
Synthetic Data Generation Blueprint Speeds Up Robot Development Pipelines Embodied AI systems, which refers to the integration of AI into physical systems, must be trained with real-world data - traditionally a complex and resource-intensive process. Each robot typically needs its own custom dataset due to differences in hardware, sensors and environments.
Synthetic data offers a powerful alternative. NVIDIA Isaac Lab 2.1 - the latest version of the open-source robot learning framework, announced at Automate - provides developers with tools to accelerate the robot training process using the NVIDIA Isaac GR00T Blueprint for synthetic motion generation. Built on NVIDIA Omniverse, a physical AI simulation platform, and NVIDIA Cosmos world foundation models, the blueprint provides a reference workflow for creating vast amounts of synthetic and robot manipulation data, making it easier and faster to train robots, like manipulators and humanoids, for a variety of tasks.
NVIDIA showcases the synthetic manipulation motion generation blueprint. Robotics Leaders Harness NVIDIA Technologies for Industrial AI Image courtesy of UR. Robotics leaders are building next-generation robots, tapping into NVIDIA technologies to train, power and deploy physical AI in industrial settings.
Universal Robots, a leader in collaborative robotics, introduced UR15, its fastest collaborative robot yet, featuring improved cycle times and advanced motion control. Using UR's AI Accelerator - developed on the NVIDIA Isaac platform's CUDA-accelerated libraries and AI models, and NVIDIA Jetson AGX Orin - manufacturers can build AI applications to embody intelligence into cobots.
Vention, a manufacturing automation company, announced MachineMotion AI, an automation controller designed to unify motion, sensing, vision and AI. The system taps into the NVIDIA Jetson platform for embedded computing and NVIDIA Isaac's CUDA-accelerated libraries and models, enabling compute-intensive AI tasks such as real-time vision processing, bin-picking and autonomous decision-making. This technology shows the value AI brings to the manufacturing floor for practical deployment of robotic solutions.
Standard Bots, a robotics developer, unveiled its manipulator, a 30kg-payload, 2m-reach robot that can be used for heavy-duty tooling and moving large objects in the automotive, aerospace and logistics industries. With NVIDIA Isaac Sim, a reference application built on Omniverse, robots can be taught tasks through demonstrations, eliminating the need for traditional coding or programming to free up developers for higher-value tasks. Standard Bots also announced teleoperation capabilities via a tablet device, which can efficiently collect training data.
KUKA, a leading supplier of intelligent automation solutions, unveiled its KR C5 Micro-2, a small robot controller integrated with an NVIDIA Jetson extension for AI-ready applications. It will provide future KUKA robots with better AI vision and AI-based control tasks powered by NVIDIA's software stack.
NVIDIA Brings Software to Deploy AI Agents in Factories and Warehouses In addition to robots, manufacturers everywhere are increasingly turning to AI agents capable of analyzing and acting upon ever-growing video data.
The NVIDIA AI Blueprint for video search and summarization (VSS), part of the NVIDIA Metropolis platform, combines generative AI, large language models, vision language models and media management services to deploy visual AI agents that can optimize processes, such as visual inspection and assembly, and enhance worker safety in factories and warehouses.
This helps eliminate manual monitoring and enables rapid processing and interpretation of vast amounts of video data, helping businesses drive industrial automation and make data-driven decisions. Developers can now use their own video data to try the AI Blueprint for VSS in the cloud with NVIDIA Launchable.
Industry leaders are using the blueprint for VSS to enable advanced video analytics and computer vision capabilities across domains.
At Automate, Siemens will be showcasing its Industrial Copilot for Operations, a generative AI-powered assistant that optimizes workflows and enhances collaboration between humans and AI. Using the tool, shop floor operators, maintenance engineers and service technicians can receive machine instructions and guidance quicker, using natural language. The copilot uses NVIDIA accelerated computing and NVIDIA NIM and NeMo Retriever microservices from the AI Blueprint for VSS to add multimodal capabilities.
Connect Tech, an edge computing company, is analyzing drone footage with the blueprint for VSS running on NVIDIA Jetson edge devices to enable real
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As the manufacturing industry faces challenges - such as labor shortages, reshoring and inconsistent operational strategies - AI-powered robots present a significant opportunity to accelerate industrial automation.
