Nvidia and LG are taking their long-running technology partnership into a much more physical direction: humanoid robots.

The two companies have signed a strategic agreement to work together on next-generation humanoid robotics, AI factories and smart mobility, with LG planning to unveil a new bipedal humanoid robot powered by Nvidia technology in the first quarter of 2027.

The partnership brings together two very different strengths.

Nvidia provides the artificial intelligence models, robotics software and high-performance computing needed to give machines the ability to perceive, reason and act.

LG brings decades of experience in manufacturing, electronics, components, batteries, sensors, motors and consumer products.

Together, the companies are betting that the next major stage of AI will not stay inside data centers or smartphones. It will move into factories, homes, vehicles and other physical environments.

Nvidia and LG Are Building a New Humanoid Robot

At the center of the partnership is a next-generation bipedal humanoid robot that LG is developing using Nvidia’s robotics platform.

The robot is expected to combine Nvidia’s Physical AI technologies with LG’s own robotics hardware and engineering capabilities.

LG plans to unveil the robot in the first quarter of 2027.

The project is part of a broader strategy in which Nvidia and LG are trying to accelerate the development of machines that can understand the physical world, make decisions and perform tasks alongside humans.

That is different from traditional industrial automation.

Conventional robots are often designed for specific, repetitive tasks.

Humanoid robots are intended to be much more flexible.

A successful humanoid could potentially move through environments designed for people, use existing tools and equipment, and learn to perform different tasks without requiring an entirely new factory layout.

What Nvidia Technology Will Power LG’s Robot?

Nvidia’s role is primarily focused on the robot’s AI and computing stack.

LG is developing its humanoid robot around several Nvidia technologies, including NVIDIA Isaac GR00T and NVIDIA Jetson Thor.

Isaac GR00T is Nvidia’s foundation-model platform for humanoid robots. It is designed to help robots understand their surroundings, reason about tasks and generate actions.

Jetson Thor provides the onboard computing needed to run advanced AI workloads directly on the robot.

That combination is important because humanoid robots need to make decisions in real time.

A robot cannot always send every movement or perception task to a remote data center.

It needs enough computing power locally to process sensor information, understand its surroundings and control its body.

What Is NVIDIA Isaac GR00T?

NVIDIA Isaac GR00T is a robotics foundation-model platform designed specifically for humanoid robots.

The goal is to make robots more capable of understanding the world around them and performing complex physical tasks.

Traditional robots are typically programmed for predefined movements.

For example, a factory robot may repeatedly pick up the same component and place it in the same location.

A foundation-model approach is different.

Instead of programming every possible movement individually, AI models can help robots learn general skills and adapt those skills to different situations.

That could eventually allow a humanoid robot to perform multiple tasks using the same underlying AI system.

Nvidia has been expanding the GR00T ecosystem throughout 2026, with new models and tools aimed at robot learning, simulation, reasoning and physical AI.

LG is now becoming one of the major companies using that technology for its own humanoid robotics development.

Why Jetson Thor Matters

A humanoid robot needs a powerful computer inside its body.

It has to process information from cameras and other sensors, understand its surroundings, make decisions and control motors and joints.

Nvidia designed Jetson Thor for this type of robotics workload.

The platform provides high-performance AI computing at the edge, allowing robots to perform advanced AI processing without depending entirely on cloud servers.

For LG, this provides an important foundation for building a robot capable of operating in real-world environments.

The combination of Jetson Thor and Isaac GR00T effectively gives LG access to both the robot’s computing layer and its AI development layer.

LG Will Supply More Than the Robot’s Exterior

The partnership is not simply Nvidia putting its computer inside an LG robot.

LG has its own extensive technology ecosystem that can contribute to the machine.

The broader LG Group includes businesses working on electronics, components, batteries, motors, sensors and telecommunications.

That gives LG an unusual advantage in humanoid robotics.

A humanoid robot requires much more than an AI model.

It needs:

Motors
Actuators
Sensors
Cameras
Batteries
Control systems
Mechanical components
Power management
Connectivity
Manufacturing expertise

LG can potentially supply many of these components through its different businesses.

That creates a vertically integrated approach to robotics that could become increasingly important as humanoid robots move from prototypes toward commercial production.

LG’s Robotics Components Could Become a Major Advantage

Actuators are among the most important components in a humanoid robot.

They allow the robot’s joints and limbs to move.

A robot may have excellent AI software, but without precise and efficient motors and actuators, it cannot perform useful physical tasks.

LG has significant experience developing high-efficiency motors and other components.

LG Innotek can also contribute sensing technologies, while LG Energy Solution brings battery expertise.

This creates an interesting division of responsibilities.

Nvidia provides the AI brain and computing platform.

LG provides much of the physical body and manufacturing ecosystem.

The combination could help the companies move faster from AI models to actual machines.

The Robot Is Expected to Debut in 2027

LG plans to unveil its next-generation bipedal humanoid robot in the first quarter of 2027.

That timeline makes the current partnership more than a long-term research project.

The companies are already working on the underlying technologies, and LG has been developing its humanoid robotics capabilities for some time.

LG’s CLOiD robot family is part of that broader effort.

The company has been exploring home robotics as well as industrial applications, giving it experience with both consumer environments and manufacturing environments.

The new Nvidia-powered humanoid is expected to represent a more advanced stage of that development.

LG Is Already Testing Robots in Factories

The humanoid partnership is not limited to a future robot launch.

LG is also moving toward real-world industrial testing.

The company plans to deploy its wheel-based CLOiD robots on a washing-machine manufacturing line at its Tennessee facility.

This is important because robotics companies need real-world data to improve their systems.

A robot can perform well in a laboratory but encounter completely different challenges inside an active factory.

There may be changing lighting conditions, moving workers, different objects, unexpected obstacles and variations in production processes.

Real-world factory deployments can help companies gather the data needed to train and validate physical AI systems.

Why Factory Data Is So Important

AI models learn from data.

For language models, that data comes primarily from text and other digital information.

Robots need something different.

They need data about the physical world.

That includes:

Movements
Objects
Human interactions
Physical forces
Spatial relationships
Sensor readings
Environmental changes
Successful and unsuccessful actions

This is one reason Nvidia and LG are also working on physical AI data generation and simulation.

The companies can use real-world production data together with synthetic data and simulated environments to improve robot training.

That could shorten the development cycle for future robots.

Nvidia and LG Are Building an AI Factory Too

The humanoid robot is only one part of the partnership.

Nvidia and LG are also expanding their work around AI factories.

An AI factory is essentially infrastructure designed to train, simulate and deploy AI systems at scale.

For robotics, that infrastructure can be used to:

Collect physical-world data.
Generate synthetic training data.
Train AI models.
Simulate robots in virtual environments.
Test different behaviors.
Validate performance.
Deploy the models to physical machines.

This creates a continuous development cycle between the digital and physical worlds.

The more robots operate in real environments, the more data can potentially be collected.

That data can then be used to improve future AI models.

Why Physical AI Is Becoming the Next Big AI Trend

The AI industry has spent years focusing on digital intelligence.

Large language models can write text, generate images, analyze documents and write software.

But the next frontier is getting AI systems to interact with the physical world.

That is where the term Physical AI comes in.

Physical AI refers to AI systems that can perceive and reason about the real world and then take physical actions.

Humanoid robots are one of the most visible examples.

Autonomous vehicles are another.

Industrial robots, warehouse machines and smart manufacturing systems also fall into this category.

Nvidia believes this could become a major expansion of the AI market because intelligence would no longer be limited to software.

It could be embedded into machines.

Why Humanoid Robots Need AI Foundation Models

Humanoid robots are difficult to build because the human environment is extremely complicated.

A person can walk through a room, recognize objects, pick something up, understand instructions and adjust their behavior almost automatically.

A robot needs technology to reproduce many of those capabilities.

It needs to understand:

Where objects are
How objects can be manipulated
How much force to use
How to maintain balance
How to move safely
What humans are doing
What action should happen next

A foundation model can provide a common intelligence layer that helps manage these different tasks.

That is the direction Nvidia is taking with Isaac GR00T.

Nvidia’s Bigger Robotics Strategy

LG is not Nvidia’s only robotics partner.

Throughout 2026, Nvidia has been expanding its robotics ecosystem with companies working on humanoids, industrial robots and autonomous machines.

The company’s strategy is to provide a common technology stack that robot developers can build on.

That stack includes:

Isaac robotics software
GR00T foundation models
Cosmos world models
Isaac Sim
Isaac Lab
Jetson robotics processors
Robotics safety technologies

Instead of building every component from scratch, robot manufacturers can use Nvidia’s platform and focus more heavily on their own hardware and applications.

LG’s partnership fits directly into this strategy.

Safety Will Be Critical for Humanoid Robots

Humanoid robots will eventually operate around people.

That makes safety one of the most important challenges in the industry.

A robot that can move quickly and manipulate heavy objects needs to understand not only what it should do but also what it should not do.

Nvidia has introduced Halos for Robotics, a safety architecture designed for physical AI and robotics.

The broader objective is to create safety systems that cover sensing, computing, software and physical interaction.

For LG, technologies like these could become important as its robots move from controlled demonstrations into factories and potentially homes.

Could LG Humanoid Robots Work in Homes?

Eventually, that is one of LG’s ambitions.

The company already has extensive experience with household appliances, smart-home technology and consumer electronics.

That gives it an interesting potential market for humanoid robots.

A home robot could theoretically perform tasks such as:

Carrying objects
Assisting with household chores
Moving items between rooms
Helping elderly users
Interacting with smart appliances
Performing repetitive household tasks

But the home is much harder to automate than a controlled factory.

A factory can be designed around a robot.

A home cannot.

Furniture changes.

Objects are left in different places.

People behave unpredictably.

Pets move around.

Lighting changes.

For this reason, reliable home humanoids are likely to require significantly more development and testing.

Could LG’s Robot Be Used in Factories?

Industrial applications are likely to be one of the most important early markets.

Factories are relatively structured environments.

Humanoid robots could potentially perform tasks that currently require human workers to move between different stations or handle equipment designed for people.

Possible applications include:

Material handling
Inspection
Assembly assistance
Packaging
Warehouse operations
Machine tending
Repetitive maintenance tasks

The biggest advantage of a humanoid design is flexibility.

Instead of redesigning an entire facility around a specialized machine, a humanoid could potentially operate within spaces already designed for humans.

Nvidia and LG Are Also Working on Smart Mobility

The partnership extends beyond robotics.

Nvidia and LG are also working together on next-generation mobility technologies.

LG is exploring Nvidia’s DRIVE platform for future automotive systems, including advanced driver assistance and AI-defined vehicles.

This gives the partnership three major physical AI areas:

Robots + AI Factories + Vehicles

All three require similar underlying capabilities.

They need sensors.

They need AI models.

They need high-performance computing.

They need real-time decision-making.

And they need safety systems.

That makes the partnership broader than a single humanoid robot project.

What Makes the Nvidia-LG Partnership Different?

Several companies are developing humanoid robots.

But Nvidia and LG bring a particularly interesting combination of capabilities.

Nvidia has become one of the leading suppliers of AI computing and robotics software.

LG has manufacturing capabilities, consumer electronics expertise, components, batteries, sensors and industrial operations.

This means the partnership potentially covers a large portion of the robotics stack.

From AI training to simulation.

From onboard computing to sensors.

From batteries to actuators.

From software to manufacturing.

That could help LG move faster as humanoid robotics becomes more competitive.

The Biggest Challenge Will Be Commercialization

Building a humanoid robot that can walk is one thing.

Building one that can perform useful tasks reliably and economically is much harder.

The robot needs to be:

Safe
Reliable
Energy efficient
Affordable
Easy to maintain
Capable of learning new tasks
Fast enough for real work
Durable enough for industrial environments

The economics also matter.

If a humanoid robot costs too much to purchase and maintain, businesses may prefer traditional industrial robots for specific tasks.

The real opportunity comes when one general-purpose humanoid can perform many different jobs.

That is where AI foundation models could become particularly valuable.

What Could Go Right for Nvidia and LG?

Several factors could work in their favor.

Nvidia’s AI Ecosystem

Nvidia already has a large developer ecosystem around accelerated computing and AI.

That can give robotics developers access to established software, hardware and simulation tools.

LG’s Manufacturing Experience

LG understands large-scale manufacturing and consumer products.

That experience could help turn robotics prototypes into commercially viable machines.

Physical AI Demand

As AI moves into manufacturing, logistics and homes, demand for intelligent machines could increase.

Component Integration

LG’s access to motors, actuators, sensors and batteries could reduce dependence on external suppliers.

Real-World Data

Factory deployments could provide valuable data for improving robotics models.

What Could Go Wrong?

There are also serious challenges.

Humanoid Robotics Is Extremely Difficult

Walking, balancing, manipulating objects and understanding complex environments all require advanced technology.

High Development Costs

Training robotics models and building sophisticated hardware can require significant investment.

Battery Limitations

Humanoid robots need enough energy to operate for useful periods without becoming too heavy.

Safety Requirements

A machine operating near humans must meet demanding safety standards.

Competition

Nvidia and LG are entering a rapidly developing market with numerous robotics companies already competing for technological leadership.

Commercial Demand Is Unproven

The long-term market for general-purpose humanoid robots is promising, but widespread commercial adoption is not guaranteed.

When Will We Know If the Partnership Works?

The first major milestone will be the planned first-quarter 2027 unveiling of LG’s next-generation humanoid robot.

After that, the more important question will be what the robot can actually do.

A successful demonstration would be interesting.

A robot that can reliably perform useful tasks in a real factory would be much more significant.

The next stages will likely involve pilot deployments, additional training, production validation and eventually commercialization.

The real test will be whether LG can turn Nvidia’s robotics technology and its own hardware capabilities into a machine that businesses are willing to deploy at scale.

The Bigger Picture

The Nvidia-LG partnership represents something bigger than one new robot.

It is part of a broader shift in the AI industry.

For years, AI development was largely about software.

Now companies are trying to give AI a physical body.

That means AI companies increasingly need partnerships with manufacturers, robotics companies, automotive suppliers and infrastructure providers.

Nvidia is positioning itself as the computing and intelligence layer for that new ecosystem.

LG is positioning itself as a manufacturer capable of turning that intelligence into physical products.

If the strategy works, the two companies could become important players in the emerging Physical AI economy.

Bottom Line

Nvidia and LG are moving deeper into humanoid robotics with a partnership that combines Nvidia’s AI technology with LG’s hardware and manufacturing capabilities.

The companies are developing a next-generation bipedal humanoid robot built around NVIDIA Isaac GR00T and Jetson Thor, with LG targeting a public unveiling in the first quarter of 2027.

But the partnership goes far beyond the humanoid itself.

Nvidia and LG are also working on AI factories, physical AI data generation, smart manufacturing and next-generation mobility technologies.

LG can contribute robotics components, sensors, actuators, batteries, manufacturing expertise and real-world production data, while Nvidia provides AI models, simulation tools and computing platforms.

The biggest opportunity is the possibility of creating robots that are flexible enough to perform many different tasks in environments originally designed for humans.

The biggest challenge is turning that vision into a safe, reliable and economically viable product.

If Nvidia’s Physical AI technology and LG’s manufacturing capabilities come together successfully, the partnership could become an important step toward the next generation of intelligent machines.

The first major test will arrive in 2027, when LG is expected to show the world what its Nvidia-powered humanoid robot can actually do.

FAQ

What is Nvidia and LG’s humanoid robot partnership?

Nvidia and LG are developing a next-generation bipedal humanoid robot that combines Nvidia’s robotics AI technologies with LG’s hardware, components and manufacturing expertise. LG plans to unveil the robot in the first quarter of 2027.

When will LG’s humanoid robot launch?

LG plans to unveil its next-generation humanoid robot in the first quarter of 2027. The unveiling is expected to demonstrate the company’s latest work using Nvidia’s robotics technology.

What Nvidia technology will LG’s humanoid robot use?

The robot is being developed using Nvidia’s Isaac GR00T humanoid robotics foundation model and Jetson Thor onboard computing platform. Nvidia’s broader robotics ecosystem also includes simulation, physical AI and safety technologies.

What is NVIDIA Isaac GR00T?

Isaac GR00T is Nvidia’s foundation-model platform for humanoid robots. It is designed to help robots perceive the world, reason about tasks and perform physical actions.

What is Jetson Thor?

Jetson Thor is Nvidia’s high-performance computing platform designed for advanced robotics and physical AI. It provides onboard computing for tasks such as perception, reasoning and robot control.

What will LG contribute to the robot?

LG can contribute robotics components, actuators, sensors, batteries, electronics and manufacturing expertise through its broader business ecosystem. These capabilities complement Nvidia’s AI and computing technologies.

Will LG’s humanoid robot be used in factories?

Industrial applications are an important part of LG’s robotics strategy. LG is also testing its CLOiD robots in manufacturing environments, including plans for deployment on a washing-machine production line in Tennessee.

What is Physical AI?

Physical AI refers to artificial intelligence systems that can perceive and reason about the physical world and then take actions in it. Humanoid robots, autonomous vehicles and intelligent industrial machines are examples of Physical AI.

Is Nvidia only working with LG on humanoid robots?

No. The Nvidia-LG partnership also covers AI factories and smart mobility. The companies are working on technologies related to manufacturing, data centers, autonomous driving and AI infrastructure.

Why is the Nvidia-LG partnership important?

The partnership combines Nvidia’s AI models and computing technologies with LG’s manufacturing, electronics, robotics components and real-world production capabilities. That combination could help accelerate the development and commercialization of Physical AI.