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NVIDIA Robotics
Computer Hardware Manufacturing
Santa Clara, California 493,778 followers
Inspiring visionaries and developers to create the next gen of AI-driven robots and explore the world of physical AI.
About us
The NVIDIA Robotics platform accelerates the development of AI-driven robots, streamlining processes from design and simulation to deployment. It enables key functions like navigation, mobility, grasping, and vision, supporting robotics across industries such as manufacturing, agriculture, logistics, and healthcare.
- Website
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https://www.nvidia.com/en-us/industries/robotics/
External link for NVIDIA Robotics
- Industry
- Computer Hardware Manufacturing
- Company size
- 10,001+ employees
- Headquarters
- Santa Clara, California
Updates
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A great read for anyone interested in how physical AI is transforming robotics. It also features perspectives from our VP of Robotics and Edge Computing — check it out 👇
⏩ Physical AI is moving from experimentation to execution ⚙️ We see the conversation moving from interest to impact. Advances in perception, learning, and real-time adaptation now allow robots to operate in dynamic environments where earlier automation struggled. As a result, physical AI is expanding beyond tightly controlled settings into unstructured, context-dependent work, unlocking possibilities traditional robotics couldn’t address. Organizations are no longer asking if physical AI matters, but how fast they can scale it for impact. 📘 Read more in our report: Physical AI: Taking human–robot collaboration to the next level 👉 https://bit.ly/4eiVXvu The insights will also be showcased at Hannover Messe 2026., Hall 15 | Booth F52 | 20–24 April 2026 #HannoverMesse2026 #PhysicalAI
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NVIDIA Robotics reposted this
We're releasing NVIDIA NCore - an open-source multi-sensor data platform for neural 3D reconstruction and physical AI. Autonomous vehicles, robotics, and 3D reconstruction research all depend on multi-sensor recordings from cameras, lidars, and radars. But sensor data today is fragmented across incompatible formats - every project reinvents data loading, calibration handling, and sensor projection. NCore solves this with a canonical interchange format: one unified representation for multi-sensor recordings with rigorous coordinate conventions, modular components, and a design principle of fully non-redundant storage - any signal that can be computed is computed on-demand, not baked in. What makes it different: • Extensible component-based architecture - poses, intrinsics, sensors, and labels are independent. Swap calibrations or add annotations without rewriting data. • A new streamable, cloud-native .itar storage format with O(1) random access, designed for distributed training on clusters. Read directly from S3, GCS, or Azure with no local extraction needed. • Accurate GPU-accelerated sensor models on PyTorch/CUDA with rolling-shutter-aware projection across cameras, lidars, and radars. • Built-in converters for Waymo Open, COLMAP/ScanNet++, and NVIDIA Physical AI datasets, with more being actively developed. NCore is already the production data backbone for NVIDIA NuRec, and dataset loading is integrated into 3DGRUT and gsplat. It's designed to work equally well for AV fleet data, robotics recordings, and free-posed captures. Fully open source under Apache 2.0. Install from PyPI, convert your datasets, and start building. Very proud of the team that made this possible! 💚 🔗 https://lnkd.in/dp_QTHYr 🐙 https://lnkd.in/d-ziXU7t 📦 pip install nvidia-ncore Datasets available in NCore format on HuggingFace: 🤗 NVIDIA Physical AI AV — https://lnkd.in/d3yXr4Ab 🤗 PPISP (CVPR 2026 Oral) — https://lnkd.in/d6Er6v7j #nvidia #opensource #3Dreconstruction #physicalAI #neuralrendering
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How does the physical AI ecosystem come together to scale in the real world? 🏭 Join NVIDIA’s Timo Kistner for a panel with Analog Devices, Stereolabs, and Universal Robots at the Week of Robotics in Odense, Denmark to hear how leaders across sensing, vision, and robotics are accelerating the path from prototype to production. 📅 May 6 | 12:45 p.m. CEST 📍 Main Stage Learn more: https://nvda.ws/4cPezB1 Odense Robotics
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NVIDIA Robotics reposted this
Deploying humanoids in real factories! 🤖 Another stop on the NVIDIA partner tour at the massive Siemens booth at Hannover Messe, exploring what happens when NVIDIA partners with one of the world's biggest industrial companies. Akhil Docca, Head of Robotics Product Marketing at NVIDIA explained the paradigm shift happening through their long-standing partnership with Siemens. This collaboration brings AI-driven autonomy to Siemens' existing factories, specifically in Erlangen. Two layers working together: digital twins form the basis for training robots. Simulation is critical for robot training, but it also brings together ecosystem partners like Humanoid. They're using Isaac Sim and Isaac Lab to train and simulate their robots. But robots need to find a home. The marriage is happening where these robots are now being deployed in Siemens' Erlangen factory. They've demonstrated they can work autonomously for eight-hour workloads. Because they're working through NVIDIA Omniverse Libraries, you get one seamless integration layer where different pieces come together. One partner working with the world's largest industrial partner to improve factory operations. NVIDIA helps these partners come together not only at a technology layer but also from a relationship layer. We talk a lot about dancing robots and robot demos. It's great to finally see robots picking up momentum and scaling up, and Siemens is the ideal partner when it comes to scaling in industry. HANNOVER MESSE / NVIDIA Robotics ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
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Get started building your robot workspace 👇 https://lnkd.in/gDrFg2Cf
Ready to build a work cell for your SO-101? Last week we released a new robotics learning path, which takes you from sim-to-real with the SO-101 robot using NVIDIA Isaac. But to go into reality, you need a physical lab to work in! So we designed this simple lightbox (a list of materials provided in the course) based on our digital twin provided in the course. Simple backgrounds with bright, diffuse lighting can help you debug before going to more complicated environments, especially since this one matches your digital twin. Having the same environment in sim and in reality is a great way to run experiments for your learning. It also means you can easily try our post-trained NVIDIA Isaac GR00T models on your SO-101 robot. We even provide you with a calibration analysis tool (thanks Maximilian Ofir) that lets you check your robot's calibration against ours before deploying. And importantly, you can try any of these models in sim before ever deploying to the real robot. Are you building one? I want to see it! Tag me and show us what you're up to.
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NVIDIA Robotics reposted this
Let's take a look behind the scenes of the physical AI ecosystem! 👀 Together with NVIDIA, I did a partner tour during HANNOVER MESSE, visiting ecosystem partners and highlighting their approach to physical AI. Akhil Docca, Head of Robotics Product Marketing at NVIDIA, explained how physical AI is now entering mainstream adoption. So in a nutshell, physical AI is the ability for AI to run in the physical world, making machines understand physics, perceive environments, and operate autonomously like humans do. NVIDIA's platform approach is simple. Three computers working together. One to train the brain, second to simulate, third to deploy, along with models and frameworks for developers. Their partner Wandelbots is building Wandelbots NOVA by integrating the open NVIDIA Isaac Sim framework. Using simulation as the first step in training robots solves a critical problem, training in the real world is risky, dangerous, and can't cover all scenarios you need. NVIDIA is investing heavily in end-to-end deployment, closing the sim-to-real gap. Can’t wait to publish my next stops! :) NVIDIA Robotics 💚 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
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NVIDIA Robotics reposted this
NVIDIA and Google Cloud are building the future of industrial and physical AI. 🦾 Read how Omniverse libraries and Isaac Sim, available on Google Cloud Marketplace, are allowing developers to build physically accurate digital twins and develop custom robotics simulations pipelines. 👇
Google Cloud and NVIDIA are expanding their partnership across agentic and physical AI. At #GoogleCloudNext, the companies made several announcements, including: ✅ NVIDIA Vera Rubin-powered A5X instances, scaling up to nearly 1M Rubin GPUs ✅ Gemini on Google Distributed Cloud, powered by the NVIDIA Blackwell platform ✅ First Confidential Computing NVIDIA Blackwell GPUs in the cloud ✅ Agentic AI built on Gemini Enterprise Agent Platform with NVIDIA Nemotron and NeMo Learn more ➡️ https://nvda.ws/4cr8snr
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What if one AI brain could run every robot on the planet—from a humanoid to a warehouse arm—all at once? 🧠 Deepak Pathak, CEO and Co-Founder, and Abhinav Gupta, President and Co-Founder of Skild AI, explain how they are building "OmniBrain," a universal foundation model designed to generalize intelligence across any robot form factor and task. 📺 Watch the episode: https://nvda.ws/4eD7F4d
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Join us at Week of Robotics in Odense, Denmark — the world’s cobot capital. 🤖 Hear from our VP of Robotics and Edge AI, Deepu Talla, on how the industry is evolving toward adaptive, intelligent systems — from rigid automation to machines that can perceive, adapt, and act. 📅 May 6 | 11:00 a.m. CEST 📍 Main Stage, UCL University Lillebaelt, NextGen Robotics LIVE Don't miss it → https://nvda.ws/42jyp2m Odense Robotics
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