This National Robotics Week , NVIDIA is highlighting the breakthroughs that are bringing AI into the physical world — as well as the growing wave of robots transforming industries, from agricultural and manufacturing to energy and beyond.
Advancements in robot learning, simulation and foundation models are accelerating development, enabling robots to move from training in virtual environments to real-world deployment faster than ever.
With NVIDIA platforms for simulation , synthetic data and AI-powered robot learning , developers now have the tools to build machines that can perceive, reason and act in complex environments.
Check back here all week for coverage on the latest NVIDIA physical AI technologies.
To bring robots into everyday life, researchers at the University of Maryland are developing AI-powered humanoid systems capable of performing complex household tasks with greater autonomy.
NVIDIA RTX PRO 6000 Blackwell GPUs for training large models and NVIDIA Jetson AGX Thor developer kits for efficient deployment on physical robots help bridge the gap between research and real-world applications.
The second cohort of the Amazon Web Services (AWS) MassRobotics fellowship comprises startups being recognized for compelling industrial use cases harnessing robotics and computer vision . They will receive access to technical resources and AWS cloud credits.
The cohort includes NVIDIA Inception members Burro, Config Intelligence, Deltia, Haply Robotics, Luminous Robotics, Roboto AI, Telexistence, Terra Robotics and WiRobotics, each developing technologies spanning humanoid robotics, industrial automation, haptics and agricultural systems.
Burro creates autonomous agricultural robots for tasks like grape harvesting and crop scouting.
Config Intelligence builds data infrastructure for general-purpose bimanual robotics to enable reliable two-handed tasks in real-world settings.
Deltia provides AI-driven manufacturing intelligence that optimizes assembly lines using computer vision and analytics.
Haply Robotics designs haptic control devices that serve as “steering wheels” for physical AI systems across industries.
Luminous Robotics deploys AI-powered robotic systems for fast, low-cost solar-panel installation and maintenance.
Roboto AI offers a data-analytics platform that accelerates robot development by managing and analyzing robotics data.
Telexistence develops AI-powered humanoid robots and remote-controlled systems for retail and logistics.
Terra Robotics develops laser-weeding agricultural robots to automate sustainable farming.
WiRobotics creates wearable walking-assist and humanoid robots to enhance mobility and physical interaction, using training data from assisted products to train its humanoids.
Maximo , a solar robotics business incubated within The AES Corporation, recently completed a 100-megawatt solar installation using its robot fleet. Developed with NVIDIA accelerated computing, NVIDIA Omniverse libraries and the NVIDIA Isaac Sim framework , Maximo demonstrated that autonomous installations can operate reliably for utility-scale projects.
The solution improves installation speed, safety and consistency, helping close the gap between rising demand for faster time to power and construction capacity.
As solar expansion faces ongoing labor constraints and rising demand, AI-driven field robotics systems like Maximo are helping accelerate infrastructure buildout, reduce costs and redefine how energy projects are delivered.
To help regenerate the Earth, Aigen’s solar-powered autonomous robots are breaking farmers’ dependency on chemicals through precision weed control powered by vision AI.
The NVIDIA Inception startup is building a new kind of farming system that’s powered by clean energy and continuously enriched by data. Aigen’s fleet of solar-driven rovers uses advanced computer vision to identify and remove weeds, dramatically reducing the need for herbicides.
Farming has no standard environment. Every field is different — different crops, different soil, different equipment, weeds, growth stages and geographies. That fragmentation makes real-world data collection slow, expensive and inconsistent. By post-training NVIDIA Cosmos open world foundation models on their specialized data and harnessing NVIDIA Isaac Sim pipelines, Aigen is building the system that generalizes for millions of agriculture scenarios.
On the ground, each rover runs inference using an NVIDIA Jetson Orin edge AI module to distinguish crops from weeds in real time.
Using these rovers, farmers can grow crops more sustainably and profitably, using regenerative practices that heal the land and foster ecological balance.
Learn about the breakthroughs shaping the next chapter of AI anytime, anywhere.
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://blogs.nvidia.com/blog/national-robotics-week-2026/#primary
- https://blogs.nvidia.com/blog/author/nvidiawriters/
- https://blogs.nvidia.com/blog/national-robotics-week-2026/#disqus_thread
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Informational only. No financial advice. Do your own research.