#nvidiaisaac

[govindhtech]

NVIDIA Omniverse, Isaac, & Metropolis Fuel AI-Driven Change

At a Toyota facility, robots move heavy metal. Yaskawa’s robots coexisting in factories with human employees. Rikei Corporation creates digital twin tools to support planning in order to virtually promote initiatives such as these.

As if that weren’t enough, Seven & i Holdings, a diverse retail holding firm, is improving consumer experiences by using digital twin simulations.

With the help of NVIDIA Omniverse, Isaac, and Metropolis, physical and industrial AI are advancing Japan’s industrial behemoths into the future. This week’s NVIDIA AI Summit Japan features such groundbreaking innovations in robotic manipulation, industrial inspection, and digital twins for human aid.

The timing of generative AI-driven robotics advancements couldn’t be more ideal. Japan needs advanced robots owing to its shrinking population. A Japan Times analysis predicts an 11 million employment gap by 2040.

Today, a three-computer solution that facilitates robot AI model training, testing, simulation, and deployment is speeding up industrial and physical AI-based systems.

Looking Into the Future With Toyota Robotics

To enhance its metal forging capabilities, Toyota is using NVIDIA Omniverse for physics simulation for robot motion and grip. The time needed to train robots to move forging materials is being shortened as a result.

Toyota is confirming that it can accurately replicate their robotic job handling and robot movements using NVIDIA PhysX with Omniverse. Building physical AI to power next-generation autonomous systems requires the ability to model digital twins of factories and other settings that faithfully replicate the physical properties of real-world items and systems. NVIDIA Omniverse makes this possible.

Toyota can simulate mass attributes, gravity, and friction using Omniverse so that test results may be compared to physical representations. Manipulation and robot motion may benefit from this.

For problems requiring a high level of competence, it also enables Toyota to use robots to mimic the knowledge of its top staff. Additionally, since industrial workers are not obliged to operate in the hot temperatures and hostile conditions typical of metal-forging manufacturing lines, it improves safety and productivity.

Driving Automation, Yaskawa Harnesses NVIDIA Isaac 

Yaskawa is a well-known worldwide robotics producer with over 600,000 sold and about 200 different robot types, including collaborative, dual-arm, and industrial robots for the automotive sector.Image credit to NVIDIA

With its MOTOMAN NEXT adaptable robot, the leading robotics company in Japan is entering new areas by advancing task adaption, variety, and flexibility. Yaskawa’s adaptive robots, powered by cutting-edge robotics made possible by the NVIDIA Isaac and Omniverse platforms, are aimed at automating the food, logistics, healthcare, and agricultural sectors.

Yaskawa is adding AI to its industrial arm robots so they can do a variety of industrial automation tasks by using NVIDIA Isaac Manipulator, a standard workflow comprising NVIDIA-accelerated libraries and AI models.

For accurate 6D posture estimate and tracking, Yaskawa uses FoundationPose. Yaskawa’s robotic arms are more flexible and efficient thanks to their AI models, and their motion control allows for a sim-to-real transfer, making them useful for completing challenging jobs in a variety of sectors.

Yaskawa uses Omniverse-based NVIDIA Isaac Sim digital twins and robotics simulations to save time and money. This will speed up the development and implementation of Yaskawa’s robotic solutions.

Creating Customer Experiences at Seven & i Holdings With Omniverse, Metropolis

One of the most diverse retail holdings corporations in Japan is Seven & I Holdings. Using digital simulation, the Japanese retail corporation conducts a proof of concept to comprehend consumer behavior at its retail locations.Image credit to NVIDIA

In order to better understand how its retail locations operate, Seven & i Holdings is advancing its research efforts by using NVIDIA Omniverse and NVIDIA Metropolis. Store operations are examined using computer vision models using NVIDIA Metropolis, a suite of developer tools for creating vision AI applications, which contributes to increased productivity and security. Using Blender assets and SideFX Houdini animations, an NVIDIA Omniverse based program creates a digital replica of this setting.

It may provide practical behavioral insights about retail settings and consumer interactions by combining digital twins with pricing recognition, item tracking, and other AI-based processing. Personalized advertisements may be dynamically generated and shown on customer-targeted digital signage displays using this information.

The company intends to react to consumer preferences based on data in a way never seen before by using Metropolis and the NVIDIA Merlin recommendation engine architecture to provide personalized recommendations for each individual client.

Virtually Revolutionizing, Rikei Corporation Launches Asset Library for Digital Twins

Rikei Corporation is a systems solutions provider that focuses on extended reality and spatial computing for the industrial industry.

JAPAN USD Factory is a digital twin asset library created by the technology firm especially for the Japanese manufacturing sector. JAPAN USD Factory was created on NVIDIA Omniverse to enable Japanese firms to more easily create digital twins of their factories and warehouses by digitally replicating common materials and equipment found in production facilities around Japan.Image credit ti NVIDIA

In order to increase efficiency using digital twins, Rikei Corporation wants to simplify several phases of design, simulation, and operations for the manufacturing process.

JAPAN USD Factory, which was created using OpenUSD, a global 3D asset exchange, gives developers access to its asset libraries for palettes and racks, facilitating smooth tool and process interaction.

Nvidia Omniverse pricing

Nvidia Omniverse cost depends on user type and subscription package. A summary:

Omniverse for Individuals: Nvidia offers a free version of Omniverse with basic features. This edition suits solo users, freelancers, and personal projects.

Omniverse Enterprise offers expanded functionality for multi-user collaborative workflows for enterprises. Omniverse Enterprise costs $1,800 per user yearly. Companies additionally require a Nucleus server for data sharing and asset management, which costs more:

The Nucleus server costs $25,000 for small businesses with 25 users.

Nucleus servers cost $250,000 for large enterprises exceeding 500 users.

Extended Access and Support: Nvidia offers corporate customers RTX Virtual Workstation support, specialized enterprise support, and Blender, Maya, and Unreal Engine connections.

Creative studios and big teams using 3D processes and visualization may use these services for scaled real-time collaboration.

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[therobotstudio-blog]

Jetson Nano flashed and ready to be programmed ! #jetsonnanodeveloperkit #jetsonnano #nvidiajetson #nvidiaisaac #the_robot_studio #therobotstudio #ai #artificialintelligence #robots #robotics #reinforcementlearning #technology #gpu (à Lyon, France) https://www.instagram.com/p/ByQAkdYo1jm/?igshid=tskposo94jcn

[techntium-blog]

Nvidia ra mắt máy tính AI để cung cấp cho robot tự động bộ não tốt hơn

Nvidia ra mắt máy tính AI để cung cấp cho robot tự động bộ não tốt hơn

#NvidiaCorporation, #NvidiaIsaac, #NvidiaJetsonXavier Link: https://techntium.com/cong-nghe/nvidia-ra-mat-may-tinh-ai-de-cung-cap-cho-robot-tu-dong-bo-nao-tot-hon/

[govindhtech]

ROSCon 2024: Accelerating Innovation In AI-Driven Robot Arms

NVIDIA Isaac accelerated libraries and AI models are being incorporated into the platforms of robotics firms.

NVIDIA and its robotics ecosystem partners announced generative AI tools, simulation, and perceptual workflows for Robot Operating System (ROS) developers at ROSCon in Odense, one of Denmark’s oldest cities and a center of automation.

New workflows and generative AI nodes for ROS developers deploying to the NVIDIA Jetson platform for edge AI and robotics were among the revelations. Robots can sense and comprehend their environment, interact with people in a natural way, and make adaptive decisions on their own with generative AI.

Generative AI Comes to ROS Community

ReMEmbR, which is based on ROS 2, improves robotic thinking and action using generative AI. Large language model (LLM), vision language models (VLMs), and retrieval-augmented generation are combined to enhance robot navigation and interaction with their surroundings by enabling the construction and querying of long-term semantic memories.

The WhisperTRT ROS 2 node powers the speech recognition feature. In order to provide low-latency inference on NVIDIA Jetson and enable responsive human-robot interaction, this node optimizes OpenAI’s Whisper model using NVIDIA TensorRT.

The NVIDIA Riva ASR-TTS service is used in the ROS 2 robots with voice control project to enable robots to comprehend and react to spoken commands. Using its Nebula-SPOT robot and the NVIDIA Nova Carter robot in NVIDIA Isaac Sim, the NASA Jet Propulsion Laboratory independently demonstrated ROSA, an AI-powered agent for ROS.

Canonical is using the NVIDIA Jetson Orin Nano system-on-module to demonstrate NanoOWL, a zero-shot object detection model, at ROSCon. Without depending on preset categories, it enables robots to recognize a wide variety of things in real time.

ROS 2 Nodes for Generative AI, which introduces NVIDIA Jetson-optimized LLMs and VLMs to improve robot capabilities, are available for developers to begin using right now.

Enhancing ROS Workflows With a ‘Sim-First’ Approach

Before being deployed, AI-enabled robots must be securely tested and validated through simulation. By simply connecting them to their ROS packages, ROS developers may test robots in a virtual environment with NVIDIA Isaac Sim, a robotics simulation platform based on OpenUSD. The end-to-end workflow for robot simulation and testing is demonstrated in a recently released Beginner’s Guide to ROS 2 Workflows With Isaac Sim.

As part of the NVIDIA Inception program for startups, Foxglove showcased an integration that uses Foxglove’s own extension, based on Isaac Sim, to assist developers in visualizing and debugging simulation data in real time.

New Capabilities for Isaac ROS 3.2

Image credit to NVIDIA

NVIDIA Isaac ROS is a collection of accelerated computing packages and AI models for robotics development that is based on the open-source ROS 2 software platform. The forthcoming 3.2 update improves environment mapping, robot perception, and manipulation.

New standard workflows that combine FoundationPose and cuMotion to speed up the creation of robotics pick-and-place and object-following pipelines are among the main enhancements to NVIDIA Isaac Manipulator.

Another is the NVIDIA Isaac Perceptor, which enhances the environmental awareness and performance of autonomous mobile robots (AMR) in dynamic environments like warehouses. It has a new visual SLAM reference procedure, improved multi-camera detection, and 3D reconstruction.

Partners Adopting NVIDIA Isaac 

AI models and NVIDIA Isaac accelerated libraries are being included into robotics firms’ platforms.

To facilitate the creation of AI-powered cobot applications, Universal Robots, a Teradyne Robotics business, introduced a new AI Accelerator toolbox.

Isaac ROS is being used by Miso Robotics to accelerate its Flippy Fry Station, a robotic french fry maker driven by AI, and to propel improvements in food service automation efficiency and precision.

Using the Isaac Perceptor, Wheel.me is collaborating with RGo Robotics and NVIDIA to develop a production-ready AMR.

Isaac Perceptor is being used by Main Street Autonomy to expedite sensor calibration. For Isaac Perceptor, Orbbec unveiled their Perceptor Developer Kit, an unconventional AMR solution.

For better AMR navigation, LIPS Corporation has released a multi-camera perception devkit.

For ROS developers, Canonical highlighted a fully certified Ubuntu environment that provides long-term support right out of the box.

Connecting With Partners at ROSCon

Connecting With Partners at ROSCon Canonical, Ekumen, Foxglove, Intrinsic, Open Navigation, Siemens, and Teradyne Robotics are among the ROS community members and partners who will be in Denmark to provide workshops, presentations, booth demos, and sessions. Highlights consist of:

“Nav2 User Gathering” Observational meeting with Open Navigation LLC’s Steve Macenski.

“ROS in Large-Scale Factory Automation” with Carsten Braunroth from Siemens AG and Michael Gentner from BMW AG

“Incorporating AI into Workflows for Robot Manipulation” Birds of a Feather meeting with NVIDIA’s Kalyan Vadrevu

“Speeding Up Robot Learning in Simulation at Scale” Birds of a Feather session with Macenski of Open Navigation and Markus Wuensch from NVIDIA on “On Use of Nav2 Docking”

Furthermore, on Tuesday, October 22, in Odense, Denmark, Teradyne Robotics and NVIDIA will jointly organize a luncheon and evening reception.

ROSCon is organized by the Open Source Robotics Foundation (OSRF). Open Robotics, the umbrella group encompassing OSRF and all of its projects, has the support of NVIDIA.

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[govindhtech]

Double Omniverse Isaac Sim NVIDIA GPUs on AWS Help Robots

The pace at which more intelligent robots are developed on the cloud is about to accelerate

With the arrival of NVIDIA Isaac Sim and NVIDIA L40S GPUs on Amazon Web Services, developers will be able to create and implement accelerated robotics applications in the cloud. Developed on the NVIDIA Omniverse development platform for creating and integrating OpenUSD applications, Isaac Sim is an extendable simulator for robots with artificial intelligence capabilities.

The L40S GPU is designed to power the workloads of the next generation of data centers by combining powerful AI compute with media acceleration and graphics. The L40S, which is based on the Ada Lovelace architecture, boosts engineering and robotics teams by enabling rapid real-time rendering and giving up to a 3.8x performance leap for Omniverse compared with the previous iteration.

Using Isaac Sim, the generational leap in acceleration yields 2x quicker performance than the A40 GPU across a wide range of robotic simulation workloads.

Additionally, L40S GPUs can be used for generative AI tasks, such as real-time inferencing for chat and text-to-image applications, and fine-tuning massive language models in a matter of hours.

Roboticists will be able to quickly access preconfigured virtual machines to run Isaac Sim workloads thanks to new Amazon Machine Images (AMIs) on the NVIDIA L40S in the AWS Marketplace.

The advancement of robotics in simulation is accelerating application deployment, boosting sectors like retail, food processing, manufacturing, logistics, and more.

According to ABI Research, revenue from mobile robots in warehouses is predicted to soar, more than triple from $11.6 billion in 2023 to $42.2 billion by 2030.

Robotic devices have been crucial in helping fulfillment centers satisfy the demands of online buyers while also giving workers a better work environment. Over 750,000 robots have been installed by Amazon Robotics in its facilities worldwide in an effort to enhance the working conditions for both its customers and staff who assist package fulfillment.

“They develop, test, and deploy they robots in a way that depends heavily on simulation technology,” stated Brian Basile, head of virtual systems at Amazon Robotics. They at Amazon Robotics are always expanding the scope and intricacy of they models. They will continue to push the limits of rendering, simulation, and model training with the new AWS L40S offering.

Using Isaac Sim to Hasten the Development of Robots

Large datasets may be required by robotics systems in order to operate precisely in deployed applications. Acquiring these datasets and putting them through real-world testing is an expensive, time-consuming, and unrealistic process.

AI-based robotic applications are trained and tested using robotics simulation. Simulations are making virtual advancements possible like never before with synthetic data. Prior to operation, simulations can aid in the verification, validation, and optimization of robot designs, systems, and algorithms. In order to maximize efficiency and lower the cost of manufacturing change orders, it can also be utilized to optimize facility designs prior to the commencement of construction or remodeling.

Teams may work together more successfully using Isaac Sim’s cloud access and access to the newest robotics simulation tools and features. Machine learning engineers may create production-ready synthetic datasets for training resilient deep learning perception models in Isaac Sim by utilizing the Omniverse Replicator synthetic data generation engine.

Adoption of Isaac Sim by Customers on Amazon

Among the AWS early adopters of the Isaac Sim platform are Theory Studios, Amazon Robotics, and Soft Robotics.

In order to automate, optimize, and plan its autonomous warehouses in virtual environments before deploying them in the real world, Amazon Robotics has started utilizing Omniverse to create digital twins.

Amazon Robotics will improve its Proteus autonomous mobile robot and expedite its development by using Isaac Sim for sensor emulation. This will help the online retail giant handle fulfillment more effectively.

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