Robot Magazine is pleased to welcome a special contribution from Dr. Gleb Tsipursky, a leading behavioral scientist and internationally recognized expert on AI adoption. Named the “Office Whisperer” by The New York Times, he examines a critical issue for the next generation of Physical AI: how organizations can learn from near-misses before autonomous machines scale across factories, laboratories and workplaces.

PHYSICAL AI NEEDS A NEAR-MISS LEDGER BEFORE AUTONOMOUS MACHINES SCALE

Anthropic’s August 27 research preview of the Model Hardware Standard moves AI agents another step out of software and into the physical world. The proposed standard lets agents operate programmable equipment including microscopes, liquid handlers, lasers, and robotic arms, coordinate multiple devices, adjust parameters during a workflow, and in some cases recover from hardware errors without human intervention.

That progress changes the safety problem. When an AI assistant drafts a bad paragraph, the failure is usually visible and reversible. When an agent controls physical equipment, the consequences can include damaged materials, lost production time, spoiled experiments, unsafe motion, or a chain of small deviations that eventually becomes a serious incident.

Traditional safety systems already record accidents, breakdowns, and maintenance events. Physical AI needs one additional layer: a near-miss ledger that records moments when an autonomous system was heading toward a bad outcome but a person, safeguard, or other system caught the problem first.

Near-misses are especially valuable for adaptive systems because they reveal where nominal success hides fragile judgment. If the machine completed the task only because a technician intervened, the final “success” metric can erase the most important evidence about the system.

Consider a robotic arm that reaches toward the wrong tray and stops because an operator notices the path. Production continues, so the event may never enter a failure log. Yet the episode contains information about perception, task context, human vigilance, and whether the same error could recur when nobody is watching closely.

A useful near-miss ledger would capture five things.

First, record the intended action. What was the agent trying to do, and what authority had it been given? A vague entry such as “robot error” tells the next operator almost nothing. The record should identify the task, the decision the system made, and the physical action it attempted.

Second, record the operating context. Physical systems behave differently across lighting, temperature, load, equipment state, workspace layout, and other conditions. Context matters because the same model decision can be harmless in one setting and dangerous in another.

Third, record the intervention. Did a person stop the robot? Did a software limit block the command? Did another sensor contradict the agent’s interpretation? The intervention shows which control actually prevented the bad outcome.

Fourth, record the prevented consequence. This does not require pretending to know exactly what would have happened. A short description such as “possible collision with adjacent fixture” or “wrong reagent likely to enter process” is enough to classify the risk without inflating certainty.

Fifth, record the corrective change. The point is not merely to accumulate warnings. Teams should note whether they changed a threshold, revised an instruction, altered the physical setup, added a sensor check, narrowed the agent’s permissions, or determined that no change was necessary after review.

This is a different mindset from treating human intervention as an embarrassing exception. In early physical-AI deployments, intervention is part of the learning system. A worker who notices that the machine is about to make a mistake is producing operational data that developers cannot get from successful runs alone.

That matters as integration gets easier. Anthropic says its Model Hardware Standard can reduce hardware integration that normally takes weeks or months to hours or minutes. Lower integration costs should expand experimentation. They can also increase the number of settings in which an agent encounters unfamiliar combinations of equipment, workflows, and environmental conditions.

Robot Magazine’s recent overview of Spain’s robotics market points in the same direction. Robotics is spreading across automotive production, food and beverage, logistics, healthcare, and service applications, while cobots and AI integration are broadening the range of tasks machines can perform. As robots move beyond tightly controlled, repetitive cells, the number of meaningful edge cases grows.

The near-miss ledger should therefore become a leading indicator, not an archive nobody reads. Managers can review patterns weekly or monthly: Which tasks generate the most interventions? Which safeguards catch problems? Are near-misses falling after corrective changes? Are operators repeatedly compensating for the same weakness? Do some locations or shifts encounter more edge cases than others?

These questions create a better scaling signal than raw uptime. A system can show excellent uptime while depending heavily on invisible human rescue. If those rescues are not counted, leaders may automate more aggressively precisely because people are quietly preventing failures.

The ledger also improves the relationship between frontline workers and robotics teams. Operators often know where a system is brittle before formal metrics show it. Giving them a simple way to record near-misses turns that tacit knowledge into evidence. It also reduces the incentive to hide interventions in order to make a pilot look cleaner than it really is.

The mechanism should stay lightweight. If documenting a near-miss requires a long investigation, workers will skip it. A short structured entry, ideally generated partly from machine logs and confirmed by the person involved, is enough for most cases. Serious patterns can then trigger deeper review.

Physical AI will not become trustworthy because every possible failure is predicted in advance. Dynamic environments make that impossible. Trust will come from building systems that notice weak signals, preserve evidence from interventions, and improve before those signals become injuries, shutdowns, or costly mistakes.

As agents gain the ability to operate more kinds of hardware, organizations will need to learn faster than the machines spread. A near-miss ledger gives them a practical way to do that.

Cet article Physical AI Needs a Near-Miss Ledger Before Autonomous Machines Scale est apparu en premier sur Robot Magazine.

A study published in 2025 examining 303 accidents involving human–robot interactions notably highlights unexpected robot activations and sensor errors. With the emergence of Physical AI, artificial intelligence errors are gradually moving beyond screens and entering the physical world.

For several years, we have grown accustomed to artificial intelligence making mistakes.

A chatbot invents information. An image generator produces an anomaly. A model misinterprets a document.

In most cases, the error remains digital.

With Physical AI, this situation changes radically

When artificial intelligence controls a robotic arm, a mobile robot or, in the future, a humanoid robot, a misinterpretation of its surroundings can trigger a real physical action.

An error of just a few centimetres can have consequences far more serious than a ChatGPT hallucination.

303 accidents analysed

A study published in 2025 in the scientific journal Safety Science analysed 303 accident reports involving interactions between humans and robots.

The researchers identified seven major categories of incidents.

Two phenomena stand out in particular: unexpected robot activations and sensor-related errors.

This is precisely one of the challenges that Physical AI will need to address.

A robot must perceive its environment before it can act.

Cameras, proximity sensors, vision systems, contextual data and artificial intelligence models become its eyes and, to some extent, its decision-making system.

But what happens when that perception is incorrect?

A wrong decision becomes a physical movement

Consider an extremely simple scenario.

A robot equipped with a camera must identify a crate and move it.

Its vision system misinterprets the scene.

The software nevertheless decides that it has identified the correct object.

In a conventional computer system, this error might produce incorrect data.

In a robot, it can potentially produce an incorrect physical movement.

If an operator is standing in its path, the algorithmic error becomes a safety issue.

With Physical AI, an artificial intelligence
error no longer produces only an incorrect
answer. It can produce a physical
movement.

Accidents are already a reality

Data from the United States provide a tangible measure of this risk.

In its report on workplace accidents in the manufacturing industry, the US Occupational Safety and Health Administration identified 550 incidents involving robots.

In 33% of cases, the victims were treated in emergency departments, while 2% of incidents required hospitalisation.

Reported injuries included cuts, bruises and fractures.

Robot maintenance and cleaning also appear to be particularly sensitive situations.

Of course, not all these accidents can be attributed to artificial intelligence.

That distinction is essential.

However, they demonstrate what can happen when humans and machines capable of powerful movements share the same environment.

Physical AI is now adding a new variable: the machine’s decision-making autonomy.

From software bug to physical risk

This is probably one of the major changes that the robotics industry will need to address in the coming years.

Conventional software follows relatively deterministic logic.

New generations of robots will be increasingly capable of interpreting their surroundings, adapting their actions and making certain decisions in real time.

This capability is precisely what makes them valuable.

But it also creates a new problem.

How can we guarantee the safety of a machine when not all of its decisions can be predicted in advance?

The question becomes even more important with humanoid robots.

Unlike industrial robots, which have traditionally operated behind safety barriers, humanoid robots are specifically designed to work in environments created for humans.

• Factories
• Warehouses
• Hospitals
• Shops
• And potentially, in the future, our homes

Robot errors are becoming a new KPI

Until now, manufacturers have mainly measured availability, productivity, breakdowns and accidents.

Physical AI could introduce a new indicator:
the number of incorrect decisions made by a robot before they result in an incident.

A robot operating for 1,000 hours without an accident may appear extremely reliable.

But if an operator had to intervene 30 times to prevent an incorrect action, the risk assessment becomes very different.

These “near misses” could become an essential metric for assessing the true reliability of autonomous robots.

Accidents tell us what went wrong.
Near misses could show us what may
go wrong tomorrow.

Data remains insufficient to anticipate the risk

The problem is that organisations do not yet have a common language for measuring these situations.

An emergency stop, a trajectory corrected by an operator, an incorrect detection or a collision avoided by only a few centimetres are not always recorded in the same way.

Yet these events could provide the most useful warning signs before an accident occurs.

For example, a robot recording zero accidents over 1,000 operating hours does not present the same level of risk if it required zero, 10 or 30 human interventions to prevent a dangerous action.

The next generation of indicators will therefore probably need to distinguish between:

• Accidents resulting in injury
• Property damage
• Emergency stops
• Perception errors
• Unexpected activations
• Preventive human interventions
• Near misses with no consequences

Without this level of detail, companies risk underestimating the true danger posed by systems that appear to be functioning correctly.

The next battle for Physical AI may be about trust

Robot performance is advancing rapidly.

But if millions of autonomous machines are to work alongside humans every day, their intelligence will need to be more than just efficient.

It will need to be predictable, controllable and capable of failing without putting people at risk.

Artificial intelligence introduced us to a new category of error: hallucinations.

Physical AI now confronts us with a much more tangible question: what happens when a hallucination becomes a physical movement?

Anticipating the risk before the first major accident

The question is no longer whether autonomous robots will make mistakes.

They will.

The real question is whether we will be able to detect those errors early enough to prevent them from becoming accidents.

How should near misses be recorded? What thresholds should trigger a shutdown or a system reassessment? How can an AI model be tested in unpredictable physical environments? Who should be held responsible when an autonomous decision causes harm?

These issues already concern manufacturers, robotics integrators, safety managers, insurers, researchers and regulators.

At Robot Magazine, we want to open this discussion with the organisations and experts developing, deploying and regulating Physical AI.

If you work on autonomous robot safety, near-miss detection, embedded AI system certification or the prevention of human–robot risks, please contact us.

Together, we can begin defining the methods, indicators and best practices needed to anticipate this future challenge before it becomes a crisis.

Cet article Robotics: When an AI Error becomes a Physical Risk est apparu en premier sur Robot Magazine.

Humanoid robots, quadruped robots, AMRs, cobots, cleaning robots, inspection robots and service robots are already available and are increasingly being offered internationally.

However, selling a robot in Europe is not simply a matter of shipping it from Shenzhen or Shanghai.

Manufacturers need to present it to customers, integrate it into their environments, provide maintenance, train users and, in some cases, adapt the solution to the requirements of the European market.

This is where a new challenge emerges: finding the right distributors and integrators in Europe.

From Chinese Manufacturer to International Player

China now has an exceptionally dynamic robotics ecosystem.

Companies such as Unitree Robotics, UBTECH, AgiBot, DEEP Robotics, LimX Dynamics and Fourier Intelligence are developing robots whose applications are beginning to extend far beyond the Chinese market.

This trend is particularly visible in humanoid robotics.

For many years, humanoid robots were primarily research projects or technology demonstrators. They are now entering a new phase marked by their first industrial and commercial deployments.

This evolution is forcing manufacturers to reconsider their international presence.

Europe is naturally one of their most strategic markets.

Why Europe Is So Attractive to Robot Manufacturers

Europe has highly developed industries in sectors such as automotive manufacturing, aerospace, logistics, energy, pharmaceuticals, food processing and general manufacturing.

It also has a long-established network of automation and robotics integrators.

For a foreign manufacturer, gaining access to this market can therefore represent a considerable opportunity.

However, Europe is also a fragmented market.

Selling a robot in Germany, France, Italy or Spain often requires a local commercial presence and a strong understanding of the needs of industrial companies in each country.

Certification, safety, maintenance and technical support must also be addressed.

A manufacturer may have an excellent robot and still struggle to generate sales without the right local network.

For Chinese manufacturers, entering Europe is not simply about finding customers. They need to build a network capable of selling, integrating and maintaining their robots locally.

Integrators are becoming an essential part of the equation

This is one of the key differences between selling an electronic product and selling a robot.

A robot generally needs to be integrated into an existing environment.

Consider the example of a quadruped robot designed to inspect an industrial site.

The manufacturer supplies the robotic platform. However, thermal cameras, sensors, supervision software or the customer’s IT systems may also need to be connected.

The robot then needs to be installed, its missions configured and the customer’s teams trained.

The same challenge applies to a humanoid robot in a factory or an AMR in a warehouse.

This is precisely the role of an integrator.

For Chinese manufacturers seeking to accelerate their expansion in Europe, finding integrators capable of understanding their technology and deploying it at customer sites is therefore becoming just as important as finding customers.

Which robots need European partners?

The search for partners involves several categories of robots.

Humanoid robots

This is currently one of the most closely watched segments.

Chinese manufacturers are developing humanoid robots for research, industry, logistics and, increasingly, service applications.

Their deployment will require partners capable of transforming a robotic platform into a genuine business solution.

Quadruped robots

Industrial inspection, energy, security, mining and infrastructure: quadruped robots already have several practical applications.

Once again, however, the robot alone is not enough. Integrating sensors and software represents a significant part of the solution’s final value.

AMRs and logistics robots

Logistics is probably one of the most mature markets for Asian manufacturers.

European warehouses represent a significant opportunity, but projects often require integration with existing warehouse management systems.

Service robots

Hospitality, restaurants, retail, cleaning, healthcare and reception services: many Chinese manufacturers already offer solutions for these sectors.

In these markets, local distributors play an essential role in providing demonstrations, installation and after-sales support.

Chinese manufacturers to watch

Several companies illustrate the international expansion of China’s robotics industry.

Unitree Robotics has become one of the most visible Chinese robotics brands internationally, thanks to its quadruped robots and, more recently, its humanoid robots.

UBTECH Robotics develops humanoid robots for industrial applications and is accelerating its international expansion.

AgiBot is another highly ambitious new Chinese player in the humanoid robotics market.

DEEP Robotics specialises in quadruped robots designed primarily for inspection and challenging industrial environments.

LimX Dynamics develops a range of robotic platforms, including humanoid and legged robots.

Fourier Intelligence, historically positioned in rehabilitation and medical robotics, is also developing its own humanoid platform.

This list is far from exhaustive.

China now has a significant number of manufacturers capable of offering their technologies internationally.

The next battle will therefore probably not be purely technological.

It will also be commercial and geographical.

An opportunity for European integrators

For integrators, this new generation of manufacturers may also represent a significant opportunity.

For several decades, the European industrial robotics market was built around a relatively limited number of major brands.

The arrival of new players is gradually changing the situation.

Integrators can gain access to new platforms, address applications that were previously difficult to automate and, in some cases, secure distribution agreements within their territories.

Some could become the European representatives of brands that are still relatively unknown today.

The technology industry has already experienced this scenario several times.

Companies that establish the right partnerships early enough may benefit from the manufacturer’s future growth.

Humanoid robots, quadrupeds, AMRs
and service robots are opening up new
opportunities for European integrators.

Robot Magazine aims to connect manufacturers and integrators

For several years, Robot Magazine has been monitoring developments in robotics across Europe, Asia and the rest of the world.

We regularly receive information from international manufacturers seeking to present their latest technologies to the European market.

We now want to take this initiative further.

Robot Magazine is gradually building a European network of distributors, integrators and robotics professionals interested in new technologies and manufacturers.

The objective is simple: to facilitate connections between manufacturers seeking to enter the European market and professionals capable of selling, integrating and maintaining their robots locally.

Are you a robotics distributor or integrator in Europe?

Are you looking for new brands to distribute or new robotic platforms to integrate? Would you like to become visible to international manufacturers?

A new global robotics landscape is emerging

For many years, Europe, Japan and the United States dominated much of the global robotics industry.

China has now become impossible to ignore.

However, having excellent technology does not guarantee commercial success.

The next step for many Chinese manufacturers will be to build international networks capable of selling, installing, integrating and maintaining their machines.

In this new competitive landscape, European integrators could become particularly sought-after partners.

The question is therefore no longer simply which Chinese robots will arrive in Europe.

It is who will distribute and integrate them.

Cet article Chinese robots: manufacturers seek distributors and integrators in Europe est apparu en premier sur Robot Magazine.

For decades, robotics remained primarily industrial. Robotic arms performed precise tasks in perfectly controlled environments, generally kept at a distance from humans.

That model is changing rapidly.

Advances in artificial intelligence, computer vision, sensors and gripping systems are now making it possible to imagine far more versatile machines. Mobile robots, cobots and humanoids are beginning to move beyond environments in which every movement had to be programmed in advance.

This is a major shift. If robots become capable of performing a wide variety of tasks, they will no longer represent merely an industrial investment. They will gradually become a new form of workforce.

An Industrial Battle as Much as a Technological One

In the United States, investment in artificial intelligence is now extending into robotics. Considerable sums are being committed to humanoids and “Physical AI.”

China, meanwhile, is advancing with a strongly industrial approach. It possesses an advantage that is difficult to ignore: a supply chain capable of producing motors, batteries, sensors, electronics and mechanical components on a massive scale.

The competition will therefore not simply be about who can showcase the most impressive humanoid in a video.

What matters is control over the entire value chain: components, manufacturing, software, AI models, training data, maintenance and the ability to produce thousands and potentially millions of machines.

This is where Europe must position itself.

Europe Already Holds Many of the Cards

It would be wrong to suggest that Europe is absent from the robotics sector.

It has renowned manufacturers, excellent research laboratories and numerous specialised companies. Europe also benefits from one crucial advantage: a substantial industrial base.

Automotive, aerospace, logistics, energy, healthcare and food production are all sectors that could become real-world testing grounds for the next generation of robots.

The real difficulty lies elsewhere.

Europe knows how to develop remarkable technologies and companies. But when it comes to raising billions, industrialising at great speed and conquering a global market, the same obstacles repeatedly emerge: fragmentation of the European market, access to capital, regulatory complexity and insufficient coordination between countries.

This is precisely what makes the comparison with Airbus so relevant.

An “Airbus of Robotics” Really?

The expression may sound excessive. Obviously, the idea is not to bring every European robotics manufacturer together within a single group.

But the history of Airbus is worth considering.

Faced with an extremely capital-intensive industry dominated by American companies, several European countries chose to pool their industrial expertise, funding and ambitions.

Robotics could justify a similar approach.

Not necessarily to create a single European humanoid, but to secure the technologies the entire industry will require: actuators, motors, sensors, vision systems, embedded electronics, AI models designed for the physical world and control software.

The objective should be relatively straightforward: to ensure that Europe retains the ability to build and control its own robotic systems.

Airbus Was Not Created Because Europe Did Not
Know How to Build Aircraft. It Was Created Because
Europe Needed to Achieve Critical Mass. Robotics May Soon Face the Same Question.

Europe’s Future Champions May Already Exist

Talking about an “Airbus of Robotics” might suggest that a new industrial giant needs to be created from scratch.

That is probably unnecessary.

Europe already has several companies developing some of the essential building blocks of this emerging industry.

In Germany, Agile Robots is one of the companies to watch. Based in Munich and originating from research conducted at the German Aerospace Center (DLR), the company develops solutions combining artificial intelligence, robotics and industrial automation. With its Agile ONE humanoid, it has made its ambition clear: to bring this new generation of machines into industrial environments.

Also in Germany, NEURA Robotics is developing cognitive robots, cobots and humanoids with a similar ambition: creating machines capable of working more naturally alongside humans. Its 4NE1 humanoid illustrates its determination to position Germany among the leading players in Physical AI.

Spain also has a long-established company in the field: Barcelona-based PAL Robotics. For more than 20 years, it has developed humanoid, mobile and service robots for research, healthcare, industry and retail.

And many more companies could be added to this list.

Europe also has specialists in industrial automation, vision systems, sensors, semiconductors, software, mechatronics and embedded systems. Long-established industrial groups could also play a major role in this transformation.

Perhaps this is where the true idea behind an “Airbus of Robotics” lies.

Europe does not necessarily need a single company to manufacture a European robot. Instead, it may need an industrial alliance capable of bringing together its strongest players around a common architecture: hardware, critical components, artificial intelligence, training data, software and manufacturing capacity.

Airbus was not created because Europe did not know how to build aircraft. It was created because Europe needed to achieve critical mass to compete with American champions.

Robotics may soon face the same question.

Will Agile Robots, NEURA Robotics, PAL Robotics and Europe’s other champions remain individual companies operating in their respective markets, or could they one day become the building blocks of a genuine European robotics powerhouse?

When Robots Become Economic Infrastructure

Imagine this market 10 or 15 years from now.

If millions of robots are working every day in factories, warehouses, farms, hotels and healthcare facilities, each robot will represent several thousand hours of potential work every year.

At that scale, the issue becomes economic.

A company that depends entirely on a foreign supplier to automate its production also depends on that supplier for part of its ability to produce.

If entire sectors of the European economy eventually rely on machines, software and artificial intelligence models controlled from abroad, the question of sovereignty will inevitably arise.

We have already had this debate concerning semiconductors, cloud computing and, more recently, artificial intelligence.

It would be unfortunate to wait until that dependency has become firmly established before beginning to think seriously about robotics.

Manufacturing Robots May Not Be Enough

One final issue has received relatively little attention so far: who will control the work carried out by these machines?

As robots become increasingly autonomous, platforms will be needed to assign tasks to them, measure their work, supervise their activities and coordinate entire fleets.

In the future, a company may manage three types of resources: employees, artificial intelligence agents and robots.

Humans will remain essential for certain tasks. For others, an AI agent will be more effective. And whenever an action needs to be performed in the physical world, a robot may take over.

Value could therefore gradually shift towards those capable of orchestrating these different forms of work.

This may be where part of the next technological battle will take place.

We Should Not Wait Ten Years to Ask the Question

Robotic sovereignty obviously does not mean that every screw, motor or sensor must be manufactured on European soil.

It means retaining sufficient expertise, technology and industrial capacity to avoid becoming entirely dependent on decisions made elsewhere.

For now, the market remains open. Standards have not yet been definitively established, humanoids are still searching for a viable business model and many potential applications have yet to be invented.

Europe therefore still has a card to play.

But if robotics follows the path many expect, the question will soon no longer be whether robots will occupy an important place in our economy.

We will need to know who builds them, who controls their intelligence, who owns their data and who decides what they are allowed to do.

After cloud computing, semiconductors and artificial intelligence, robotic sovereignty could become one of Europe’s next major industrial challenges.

Cet article Robotic Sovereignty: Does Europe Need Its Own “Airbus of Robotics”? est apparu en premier sur Robot Magazine.

Getting a massage from a robot? Just a few years ago, the idea would probably have sounded amusing. Yet in the United States and Europe, the first machines are beginning to find their way into spas, hotels and fitness clubs.

And we are no longer talking about the traditional massage chair found in an airport.

The new generation of robots aims to reproduce part of the work performed by a massage therapist: identifying different areas of the body, applying a specific amount of pressure and following precise movements for several dozen minutes.

American company Aescape is probably the most visible example of this trend. Its system combines a massage table with two robotic arms that perform the massage while allowing the user to adjust certain settings, including pressure and the areas they want to focus on.

The company now claims more than 100 locations and is clearly targeting spas, hotels and fitness clubs.

In France, Capsix Robotics is working on a comparable approach with its iYU robot. Here again, the ambition goes beyond a simple technological demonstration. The goal is to offer wellness professionals a new way of delivering their services.

Because behind the rather spectacular image of a massage robot lies a very real economic question.

How Much Does an Hour of Massage Really Cost?

The business model of a spa is relatively simple. To sell more massages, you generally need more massage therapists.

But a therapist obviously cannot work for ten or twelve hours without interruption. Breaks, working hours, holidays, absences and, in some regions, recruitment difficulties all have to be taken into account.

A robot changes that equation.

In the United States, for example, Aescape offers 60-minute sessions for around $89, with lower prices for shorter sessions. The positioning is interesting: the goal is not necessarily to sell a luxury experience, but to make massage more readily available.

The massage robot will probably not
replace the hands of a professional. It could,
however, turn massage into a service available
almost on demand.

For a hotel or fitness club, the question then becomes very practical.

How much does the machine cost? How many sessions can it perform each day? How long does it take to recover the investment?

Those three figures will probably determine a large part of the future of this industry.

A sufficiently well-used robot could allow a facility to open additional time slots, including at times when maintaining a full team of massage therapists would be difficult.

That does not mean massage therapists are about to disappear.

The most credible scenario may be one in which two different types of services coexist.

Human massage would retain everything that gives it value: the therapist’s expertise, the ability to understand the client, adapt the treatment and, quite simply, provide the human dimension of care.

The robot could occupy a different space: short sessions, post-workout recovery, regular massages, or customers primarily looking for availability and convenience.

ROI: The Equation That Could Convince Spas

For a spa operator, the value of a robot will mainly depend on its utilization rate. Take a simple example: a machine capable of providing six one-hour sessions per day, billed at an average of €60, represents potential daily revenue of €360, or more than €9,000 per month over 26 operating days. At eight sessions per day, revenue exceeds €12,000.

Naturally, the cost of financing or leasing the machine, maintenance, electricity, the space it occupies, and the time required for customer reception and cleaning must all be deducted.

But unlike a traditional treatment room, increasing the number of sessions does not require a proportional increase in staff hours. For a spa that is regularly fully booked or struggling to hire enough professionals, this is where the model becomes interesting: the robot does not necessarily replace a massage therapist; it primarily allows the business to sell additional hours of massage.

The true measure of ROI will therefore depend less on the price of the robot itself than on the number of additional sessions it enables the business to sell every month.

An Environment Well Suited to Robotics

Massage also has one particular characteristic that makes it attractive to robotics companies: the environment is highly controlled.

The client is lying down. The robot knows its working area. Movements are relatively slow. Pressure can be measured and limited.

This is very different from the complexity faced by a humanoid robot that needs to move around a house, recognize dozens of objects and interact with an unpredictable environment.

That may be precisely why massage robots could find their market more quickly than some far more ambitious service robotics applications.

And there is no shortage of potential use cases.

Spas naturally come to mind, but so do hotels, fitness centers, sports recovery facilities and even airports.

In a gym, for example, it is easy to imagine a member booking a 20-minute session from their phone after a workout, just as they would book a group fitness class today.

In a hotel, the same equipment could make it possible to offer massages outside normal spa opening hours.

At that point, the robot becomes less of an attraction and more of a service appliance.

The profitability of a massage robot will depend
less on its purchase price than on the number of
additional sessions it allows a business to sell.

How Far Can This Go?

The line becomes more delicate when we move beyond wellness and into the medical field.

Massage and physiotherapy are obviously not the same thing.

Scientific literature on robotic massage does exist, but it remains limited. A systematic review published in 2024 identified only 17 studies that met the researchers’ criteria. Fifteen of them were still considered preliminary trials.

It is therefore far too early to present these machines as a widespread alternative to healthcare professionals.

But the development is worth watching.

Because behind robotic massage lies a much broader question for the robotics industry: how far can we automate a profession built around human touch and physical skill?

For a long time, robots mainly replaced or assisted industrial tasks: welding, assembling, moving and sorting.

They are now beginning to enter environments much closer to our everyday lives.

They clean floors, transport meals in hotels, prepare certain dishes and are now beginning to perform massages.

The success of massage robots will probably not depend on their ability to perfectly reproduce the hands of a professional.

It will depend on something far more pragmatic: does the customer accept the experience, and does the establishment make money by installing the machine?

If the answer to both questions becomes yes, massage could well become one of the first genuine mass markets for service robotics.

Cet article After Factories, Robots are Entering Spas est apparu en premier sur Robot Magazine.

For the robotics sector, this evolution is particularly significant. Artificial intelligence is no longer limited to generative models capable of producing text, code, images or video. It is increasingly moving beyond screens and into systems that interact with the physical world.

More autonomous industrial robots, machines capable of understanding their surroundings, intelligent mobile systems, autonomous vehicles and humanoid robots are all part of a broader convergence between AI and physical systems.

That convergence is one of the areas AI Everything Abu Dhabi intends to highlight this year.

A global event focused on applied AI

According to the organisers, AI Everything Abu Dhabi is expected to bring together more than 350 AI companies, startups and international technology players from over 60 countries.

The event is also set to host more than 200 investors managing approximately US$50 billion in assets, alongside more than 150 AI-focused startups.

The event therefore goes beyond the format of a conventional artificial intelligence conference.

Its ambition is to showcase technologies already being deployed in fields such as government, finance, healthcare, energy and manufacturing, with a strong emphasis on practical applications and real-world use cases.

This focus on applied AI reflects a broader shift in the market.

After several years dominated by the race to build increasingly powerful large language models, companies are now looking at how AI can be turned into systems that directly improve operations, industrial processes and infrastructure.

From generative AI to Physical AI

Among the six main technology areas highlighted by AI Everything Abu Dhabi is Physical AI, alongside robotics and autonomous mobility.

Other focus areas include intelligent infrastructure and new energy, frontier AI models, sovereign AI, enterprise and agentic AI, as well as sovereign security and quantum technologies.

The presence of Physical AI in this programme is particularly noteworthy.

Physical AI generally refers to artificial intelligence systems capable of perceiving, understanding and acting within a physical environment.

For a robot, the challenge is therefore no longer simply to generate the correct answer to an instruction.

A machine must be able to interpret its surroundings using cameras, sensors or other perception systems, understand a task, make a decision and then carry out an action in the real world.

This combination of perception, reasoning and action is now becoming one of the key development areas in advanced robotics.

It is particularly relevant to humanoid robots, autonomous mobile robots, intelligent industrial machines and robotic manipulation systems.

Robotics is entering the era of AI models

One of the major transformations currently taking place in robotics is the emergence of artificial intelligence models capable of processing several types of information at the same time.

Vision, language, audio, sensor data and human instructions can increasingly be brought together within a single architecture.

This could lead to robots that are less dependent on highly specific programming for every individual task.

Instead of following only predefined sequences, some machines can be trained to interpret instructions and adapt their behaviour according to their environment.

For industry, this represents a significant change.

Traditional robotics remains extremely effective in structured environments such as automotive welding, assembly, palletising, painting, material handling and quality control.

New generations of autonomous systems, however, are increasingly being designed to operate in much more variable and unpredictable environments.

This is where Physical AI becomes particularly important.

Agentic AI could also reshape robotic systems

AI Everything Abu Dhabi will also focus on another rapidly developing field: Agentic AI.

The event is set to feature workshops covering agentic enterprise systems, multi-agent orchestration, responsible AI, Physical AI and rapid prototyping.

AI agents are designed to go beyond simply generating a response to a prompt.

They can receive an objective, plan multiple steps, use digital tools and coordinate different actions.

In robotics, this approach opens up interesting possibilities.

An AI agent could, for example, organise a logistics operation, distribute instructions to multiple autonomous mobile robots, monitor progress and modify the plan if conditions change.

Over time, the boundary between software agents and autonomous machines may become increasingly difficult to define.

Infrastructure is becoming strategic for intelligent robotics

This new generation of systems does not depend on robots alone.

Computing power, data centres, cloud platforms, semiconductors, networks and energy infrastructure are becoming essential components of the ecosystem.

AI Everything Abu Dhabi is designed to connect these different technology layers, bringing together data infrastructure, compute capacity, energy, agentic AI, enterprise automation, quantum technologies and sovereign security.

This convergence matters greatly for robotics.

An autonomous robot may need to process certain tasks locally in order to minimise latency, while other operations, such as model training or large-scale data analysis, may require far more powerful computing infrastructure.

The next generation of intelligent machines will therefore depend not only on progress in robotics, but also on advances in processors, AI models and computing infrastructure.

Microsoft, Intel, AWS, Mistral AI and other major technology players expected

The event is set to welcome a number of major international technology companies.

Exhibitors announced include AWS, Alibaba Cloud, ASUS, Cloudflare, Dell, HPE, Intel, Microsoft, Mistral AI, Nokia, Nebius, Nutanix, Red Hat, Snowflake, SUSE and Zoho.

Although not all of these companies are directly involved in robot manufacturing, their technologies form part of the infrastructure on which modern AI increasingly depends.

The development of more AI-driven robotics relies heavily on computing capacity, cloud services, edge computing, cybersecurity and data management.

AI Everything Abu Dhabi therefore aims to bring together the different layers of this emerging technology stack within the same event.

Specialised AI models are becoming increasingly important

The event also aims to highlight the growing diversification of the artificial intelligence model landscape.

The organisers mention companies developing Arabic large language models, multimodal AI, Voice AI technologies, open-weight models and enterprise agents.

This diversification could have important implications for robotics.

Not every robot will require an enormous model containing hundreds of billions of parameters.

In many cases, industrial users may prefer smaller, specialised models capable of operating directly on a machine or within local infrastructure.

The development of more efficient models could therefore become a key factor in the wider adoption of Physical AI.

Among the companies highlighted by the event is ModelBest, creator of the MiniCPM family of relatively compact AI models.

Abu Dhabi accelerates its AI strategy

AI Everything Abu Dhabi also has a strong institutional dimension.

The Department of Government Enablement – Abu Dhabi (DGE) is presented as the Host Partner, while a number of UAE technology and academic institutions are expected to participate.

These include the Advanced Technology Research Council, the Technology Innovation Institute, the UAE Cybersecurity Council and Khalifa University.

One of the ambitions highlighted by the organisers is to demonstrate how Abu Dhabi intends to build government services and public administration increasingly around artificial intelligence.

Beyond the public sector, the UAE is also seeking to develop a wider ecosystem bringing together research, investment, computing infrastructure and technology companies.

For robotics players, this dynamic could create new opportunities in autonomous systems, industry, logistics and intelligent infrastructure.

An event worth watching for the robotics ecosystem

For Robot Magazine, AI Everything Abu Dhabi is therefore relevant far beyond the field of generative AI.

The inclusion of Physical AI, robotics, autonomous mobility, agentic AI and advanced computing infrastructure illustrates how quickly the boundaries between artificial intelligence and physical machines are beginning to disappear.

For many years, software and robotics developed as relatively separate technology domains.

That distinction is becoming much less clear.

Artificial intelligence models are increasingly involved directly in the perception, planning and decision-making processes of autonomous systems.

The key question is therefore no longer simply how far AI models will progress.

It is also what those models will be able to do once they are integrated into machines capable of acting in the physical world.

AI Everything Abu Dhabi 2026 could provide an important glimpse into that next phase.

Cet article AI Everything Abu Dhabi 2026: Physical AI, Robotics and Autonomous Systems Take Center Stage est apparu en premier sur Robot Magazine.

The latest consolidated statistics available in 2026 show, above all, that service robotics is moving beyond experimentation and finding economically viable applications in logistics, healthcare, cleaning, agriculture and other sectors.

This market can be expected to continue growing strongly throughout 2026 and the years ahead.

The global service robotics market continues to gain momentum

According to the World Robotics 2025 – Service Robots report from the International Federation of Robotics (IFR), published at the end of 2025, more than 199,000 professional service robots were sold worldwide in 2024, representing a 9% increase in one year.

This figure provides the latest major consolidated snapshot of the market available in 2026.

But behind those 199,000 units are very different market dynamics.

Professional cleaning grew by 34%. Medical robots recorded growth of 91%. Logistics exceeded 100,000 units sold, while other categories, such as hospitality robots, declined.

For industrial companies, these figures are particularly useful for identifying the sectors in which robotics is beginning to achieve genuine economic maturity.

Nearly 200,000 professional robots sold worldwide

The IFR recorded more than 199,000 professional service robots sold in 2024, up 9%.

However, this figure must be interpreted carefully.

Unlike statistics covering industrial robots, the service robotics study does not represent a comprehensive census of every machine sold worldwide.

IFR identifies 944 service robot manufacturers globally. Data in the 2025 edition is based on information collected from a sample of 293 manufacturers.

The organization also points out that the composition of this sample may change from one year to another.

The 199,000 units therefore serve primarily as a powerful indicator of market trends.

And those trends reveal accelerating demand across several very practical applications.

Cleaning: robot sales jump 34%

This is one of the most significant increases recorded by the IFR.

More than 25,000 professional cleaning robots were sold in 2024.

In just one year, sales increased by 34%.

Floor cleaning accounts for the majority of these applications.

Shopping malls, airports, hospitals, warehouses, factories, railway stations and large retail stores are particularly well suited to automation.

The areas involved are large, the tasks are repetitive, and routes are often structured enough for robots to operate for several hours with limited human intervention.

For companies, the economics are also relatively easy to measure.

A cleaning robot can operate for several hours, sometimes outside normal business hours, and perform repetitive tasks while human workers are reassigned to more complex activities.

This 34% increase illustrates a fundamental trend in robotics today: the fastest-growing robots are not necessarily the most spectacular ones.

Economic value is often found in automating simple, repetitive and measurable tasks.

The fastest-growing robots are not
necessarily the most spectacular ones,
but those with the clearest ROI.

Healthcare: 91% growth

The most impressive figure, however, comes from medical robotics.

According to the IFR, approximately 16,700 medical robots were sold in 2024, representing an increase of 91%.

Volumes remain lower than in logistics, but the momentum is remarkable.

The category includes applications related to surgery, laboratories, rehabilitation and various medical assistance systems.

It also has an important characteristic: the economic value of a medical robot can be significantly higher than that of a relatively simple service robot.

The number of units sold alone is therefore not enough to measure the economic importance of this market.

This growth mainly illustrates the widening scope of robotics applications.

After automotive manufacturing and traditional industry, robots are increasingly entering environments where precision, repeatability and assistance for professionals are critical.

Logistics: more than 100,000 robots sold

In terms of volume, however, logistics remains the heavyweight of the service robotics market.

Approximately 102,900 robots dedicated to transportation and logistics were sold in 2024, an increase of 14%.

This category alone therefore accounts for more than half of all professional service robots recorded by the IFR.

A significant proportion of this growth is linked to the development of AMRs – Autonomous Mobile Robots.

These autonomous mobile robots transport goods, components, bins or pallets inside warehouses, logistics centers and industrial facilities.

They address a very practical problem: a considerable amount of industrial working time is still spent moving goods from point A to point B.

Automating these movements can reduce non-value-added tasks while potentially increasing the availability of human operators.

New generations of AMRs also benefit from advances in sensors, machine vision, mapping and navigation software.

As a result, they can operate in environments that are considerably less rigid than those required by previous generations of AGVs.

Robot-as-a-Service lowers the investment barrier

The growth of service robotics is not driven solely by improvements in robot performance.

The business model is also changing.

According to the IFR, the fleet of professional robots operated under a Robot-as-a-Service (RaaS) model increased by 31% in 2024, exceeding 24,500 units.

In logistics, growth reached as much as 42%.

The principle is similar to SaaS in the software industry.

Instead of purchasing a robot outright and committing significant capital, a company can pay for its use through a subscription or service contract.

Depending on the provider, maintenance, software updates and various additional services may be included.

For industrial decision-makers, this development is far from insignificant.

It can potentially transform part of a robotics investment into an operating expense, while reducing the risk associated with an initial deployment.

The question then becomes less about: “How much does this robot cost?” and more about: “How much does automating this task cost me every month, and what productivity gain can I expect in return?”

Agriculture: nearly 19,500 robots

Agricultural robotics also represents a significant market.

Nearly 19,500 agricultural robots were sold in 2024, although the segment declined by 6%.

Applications include automated milking systems and various mechanized agricultural operations.

Over the medium term, several factors could nevertheless support this market: labor shortages, an aging agricultural workforce, the need to improve productivity, and advances in machine vision and artificial intelligence.

Agriculture is precisely one of the environments where advances in AI and vision technologies could unlock new applications, because robots must operate in conditions that are far less predictable than an industrial production line.

Hospitality and customer service: a market down 11%

Not every segment is growing.

More than 42,000 robots designed for hospitality and customer-facing services were sold in 2024, but sales declined by 11%.

This category includes various information, guidance, telepresence and service robots.

The decline offers an interesting lesson.

Just because a task can technically be automated does not necessarily mean that doing so provides sufficient economic value.

The sectors currently recording the strongest growth are generally those where the return on investment can be identified relatively easily: moving goods, cleaning surfaces, automating industrial operations or assisting healthcare professionals.

944 manufacturers: a market that remains highly fragmented

The IFR now identifies 944 service robot manufacturers worldwide.

One important characteristic is that approximately 80% are SMEs with fewer than 500 employees.

The sector therefore remains extremely fragmented.

Alongside large industrial groups are numerous specialists developing machines for highly specific applications: cleaning, inspection, agriculture, security, healthcare, logistics and maintenance.

This fragmentation encourages innovation but could also lead to gradual market consolidation.

As volumes increase, the requirements for financing, industrialization, international maintenance capabilities and distribution networks become increasingly important.

With more than 4.6 million industrial robots already in operation, automation has become a global production infrastructure.

Industrial robotics remains on a completely different scale

To understand the overall scale of the phenomenon, service robotics must be compared with traditional industrial robotics.

According to World Robotics 2025, 542,000 new industrial robots were installed in factories in 2024.

Annual installations have now exceeded 500,000 units for four consecutive years.

More importantly, the global operational stock has reached approximately 4.66 million industrial robots.

Asia accounted for 74% of new global installations, compared with 16% for Europe and 9% for the Americas.

China alone accounted for approximately 295,000 new installations, representing more than half of the global market.

Over the past decade, the annual number of industrial robots installed worldwide has more than doubled.

More than 700,000 industrial robots per year expected by 2028

And the trend is expected to continue.

The IFR forecast approximately 575,000 new industrial robot installations in 2025, representing growth of 6%.

By 2028, worldwide installations are expected to exceed 700,000 industrial robots per year.

This trajectory puts the 199,000 professional service robots into a much broader context.

Manufacturing, logistics, healthcare and services are gradually converging toward higher levels of automation.

In 2026, artificial intelligence becomes the next accelerator

Since the collection of the 2024 statistics, another trend has accelerated: the integration of artificial intelligence into robotic systems.

The implications are considerable.

For several decades, robots have excelled in extremely structured environments: the same parts, the same trajectories and the same operations.

Advances in AI, machine vision and models that allow machines to interpret their environment could gradually expand the number of tasks that can be automated.

This is one of the reasons behind the current interest in intelligent AMRs, robots capable of manipulating variable objects and, over the longer term, humanoid robots.

Robot density is becoming a strategic industrial indicator

Competition is also taking place between economies.

The latest data published by the IFR in 2026 indicates that Western Europe has reached a density of approximately 267 industrial robots per 10,000 manufacturing employees.

North America stands at around 204 robots per 10,000 employees.

Robot density is gradually becoming an indicator of industrial competitiveness.

In economies facing demographic aging and difficulties finding workers for certain occupations, robotics can help increase productivity without necessarily requiring a proportional increase in workforce size.

Key figures to remember

Latest global data paints a picture of a market undergoing rapid transformation:

• 199,000+ professional service robots sold: +9%
• 102,900 transportation and logistics robots: +14%
• 25,000+ professional cleaning robots: +34%
• 16,700 medical robots: +91%
• 19,500 agricultural robots: -6%
• 42,000+ hospitality and customer service robots: -11%
• 24,500+ robots operated under RaaS models: +31%
• 944 service robot manufacturers identified worldwide
• 80% of manufacturers are SMEs
• 542,000 industrial robots installed in 2024
• 4.66 million industrial robots operating worldwide
• 700,000+ annual industrial robot installations expected by 2028

The real question: where is the ROI?

The 34% increase in cleaning robotics and 91% growth in medical robotics are impressive.

But they reveal something even more important.

Service robotics is beginning to find its markets.

We are no longer dealing only with technological demonstrations. In logistics, cleaning, healthcare and certain industrial applications, companies can now build genuine business models around robotics.

The development of Robot-as-a-Service is likely to accelerate this transition further by lowering the financial barrier to entry.

For an industrial executive in 2026, the question is therefore probably no longer whether robots will transform the sector.

The question has become much more practical:

Which task can we automate today, at what cost, and with what return on investment?

With nearly 200,000 professional service robots sold, more than 4.6 million industrial robots already operating worldwide, and global installations expected to continue rising, robotics is gradually entering a new phase.

After the race for technology comes the race for ROI, in a market that continues to grow.

Cet article Robots: Cleaning Up 34%, Medical Robotics Up 91% est apparu en premier sur Robot Magazine.

A Level of Precision Impossible to Achieve by Hand

One of the main advantages of robotics is its ability to perform extremely fine movements. While the human hand generally achieves a precision of around 30 microns, robotic systems can operate with an accuracy of as little as 5 microns. This difference is crucial when working on particularly delicate structures within the eye.

By eliminating physiological micro-tremors and controlling each movement with exceptional stability, robotic systems reduce the risk of error and improve the reproducibility of surgical procedures.

Intelligent Assistance for the Surgeon

Contrary to a common misconception, the robot does not replace the surgeon. Instead, it acts as a highly sophisticated assistance platform. Seated at a console equipped with high-definition 3D visualisation, the specialist controls micro-instruments or the laser with greater precision than could be achieved manually.

The integrated systems also analyse data in real time, allowing movements to be adapted to the individual characteristics of each patient and further enhancing the safety of the procedure.

Cataract surgery is entering a new era in
which precision is now measured in
microns.

A Faster and More Precise Procedure

During robot-assisted or laser-assisted cataract surgery, several stages of the procedure can be automated with a high degree of accuracy.

The system first creates micro-incisions in the cornea and performs precise cuts in the lens using an ultra-fast laser. The clouded lens is then fragmented, or even liquefied depending on the technology used, before being removed by suction. Finally, the surgeon implants an artificial intraocular lens designed to restore the patient’s vision.

Thanks to this partial automation, the procedure often takes less than ten minutes and, in many cases, enables particularly rapid visual recovery.

A Major Advancement in Ophthalmic Surgery

The integration of robotics into cataract surgery perfectly illustrates the convergence of artificial intelligence, medical robotics and high-precision imaging. Although these technologies are still being introduced across many healthcare facilities, they are paving the way for a new generation of ophthalmic surgery that is safer, more reproducible and increasingly personalised.

A Vast Market Driving Innovation

Cataract surgery is currently the most commonly performed surgical procedure in the world. According to the World Health Organization (WHO), cataracts affect more than 94 million people and remain the leading cause of preventable blindness worldwide.

Each year, more than 26 to 30 million cataract procedures are performed, and this figure is expected to rise significantly as the global population ages. Despite these considerable volumes, access to care remains highly unequal.

The WHO estimates that one in two people requiring cataract surgery still does not have access to the procedure. Disparities are particularly severe in sub-Saharan Africa, where nearly 75% of patients requiring surgery do not receive it.

Cataract surgery perfectly illustrates the new generation of medical robotics: technology designed not to replace the surgeon, but to make every movement more precise, stable and reproducible. — Robot Magazine

In response to this growing demand, improving the productivity of operating theatres has become a major priority. Robotic platforms and new-generation lasers are specifically designed to standardise surgical procedures, reduce variability between surgeons, shorten operating times—often to between 10 and 15 minutes per eye—and improve the quality of clinical outcomes.

For medical robotics manufacturers, ophthalmology therefore represents a strategic market combining extremely high procedure volumes, exceptional precision requirements and strong potential for technological innovation. (World Health Organization)

As these platforms become more mature and accessible, they could permanently transform the treatment of millions of cataract patients around the world.

Cet article Cataract Surgery: Robotics Opens a New Era of Precision est apparu en premier sur Robot Magazine.

This vision could make Samsung one of the major winners of the next industrial revolution.

Samsung’s history in robotics did not begin with the recent rise of generative artificial intelligence. For many years, the group has invested in technologies related to autonomous mobility, sensors, computer vision, human-machine interaction and intelligent assistants. Although much of this work has remained in the background, it reflects a consistent ambition to build an ecosystem in which robots become a natural extension of the digital environment Samsung has already developed.

The company benefits from a considerable advantage that few manufacturers can claim. It already controls most of the technological building blocks required to design a modern robot. Its factories produce processors, memory chips, batteries, sensors, cameras, OLED displays, communication modules and many of the electronic components that embedded systems depend on. This vertical integration gives Samsung a rare degree of strategic independence in an industry where many companies remain heavily dependent on external suppliers.

This industrial expertise is becoming particularly important as demand for computing power grows rapidly under the influence of artificial intelligence. Tomorrow’s robots will need to continuously analyse their surroundings, recognise objects, understand natural language, interpret complex situations and make decisions in real time. These capabilities require considerable computing power, as well as components that can deliver the right balance between performance and energy efficiency. Samsung already possesses this expertise through its semiconductor operations serving data centres, smartphones and embedded systems.

While some manufacturers showcase robots,
Samsung is methodically building the ecosystem
that could make them indispensable.

The South Korean manufacturer’s approach also differs from that of many other market players. While some companies develop a robot first and then search for potential applications, Samsung starts with existing use cases and considers how robotics could improve the user experience. This philosophy is clearly reflected in Ballie, which was introduced as a mobile assistant designed to accompany people inside their homes. Behind its intentionally playful appearance, however, lies a much more ambitious technological demonstration.

Ballie was never designed as a simple living-room gadget. It embodies Samsung’s ambition to transform the connected home into a robotic environment. The robot does not replace existing equipment; it becomes its physical interface. It moves around the home, communicates with occupants, controls compatible devices, collects information about its surroundings and adapts its behaviour to each person’s habits. In this vision, robotics is no longer an isolated object but a central component of an intelligent system connecting every device in the home.

This integration model is probably at the heart of Samsung’s strategy. For several years, the group has been developing SmartThings, its platform for connected devices. Millions of compatible products are already able to communicate with one another. Introducing a mobile robot into this environment creates entirely new possibilities. It could serve as a physical presence capable of interacting with appliances, monitoring a home, assisting an elderly person or making certain everyday tasks easier. The robot would become the physical embodiment of intelligence distributed throughout the home.

However, Samsung’s real acceleration in robotics has most likely come from its closer relationship with Rainbow Robotics. This South Korean company emerged from the work of researchers at KAIST, one of the world’s leading institutions in advanced robotics. Rainbow Robotics has recognised expertise in bipedal locomotion, robotic manipulation and autonomous mobile robots. Its Hubo humanoid robot influenced several generations of researchers and demonstrated South Korea’s expertise in the field.

By becoming the majority shareholder in Rainbow Robotics, Samsung is doing far more than making a financial investment. The group is acquiring expertise, patents, teams of specialised engineers and several years of technological progress in humanoid robot development. This decision marks an important strategic shift. Samsung no longer intends to focus solely on domestic assistance robots; it is now preparing to enter the much broader market for industrial robots and, potentially, general-purpose robots.

This evolution comes at a time when artificial intelligence is fundamentally transforming robotics. For many years, robot performance was mainly limited by mechanical capabilities. Today, the difference is increasingly determined by software. Language models, computer vision and machine-learning systems now allow robots to understand instructions expressed in natural language, interpret their surroundings and adapt their behaviour to unfamiliar situations.

Samsung identified this shift very early. For several years, the company has been investing in artificial intelligence research centres located across South Korea, Europe and North America. Its objective is not merely to develop AI for smartphones or televisions, but to build a common software platform capable of powering its entire ecosystem.

A modern robot is as much a system
of semiconductors, sensors and software
as it is a mechanical machine.

The introduction of Galaxy AI illustrates this strategy perfectly. Artificial intelligence is no longer treated as an isolated feature; it is becoming a shared software layer that could eventually be used across all of the group’s devices. Within this architecture, smartphones, televisions, household appliances and future robots could gradually share the same capabilities for understanding, interaction and assistance.

The recent relationship between Samsung and the French company Mistral AI also fits into this strategy. Beyond discussions surrounding a potential financial investment, Samsung is primarily seeking to strengthen its capabilities in language models and embedded artificial intelligence. For a manufacturer aiming to develop robots capable of interacting naturally with users, privileged access to high-performance models would provide an obvious strategic advantage. Although no official announcement currently connects Mistral AI directly to Samsung’s robotics projects, the technological synergies appear particularly coherent.

Another major Samsung strength is its ability to manufacture products at an industrial scale. Many startups are capable of demonstrating impressive prototypes but lack the resources required to produce hundreds of thousands of robots. Samsung has decades of experience managing global supply chains, mass production and industrial cost reduction. If the personal robotics market were to experience growth comparable to that of smartphones, very few companies would be as well positioned to respond rapidly to demand.

This industrial capacity could also play a major role in the professional sector. Companies are increasingly looking for robotic solutions capable of interacting with human operators, navigating complex environments and integrating with existing digital systems. Thanks to its expertise in electronic components, networks, professional displays and artificial intelligence, Samsung possesses all the elements required to offer complete solutions rather than simply selling a robot.

Competitors are already responding to this strategy. Tesla continues to develop Optimus with the ambition of progressively automating manufacturing tasks. Figure AI is expanding its partnerships with industrial companies, while Chinese manufacturers are accelerating their investments in humanoid robotics. However, the global competition will not be determined solely by the mechanical quality of the machines. It will depend on the ability to integrate artificial intelligence, control critical components and build a coherent ecosystem connecting robots, connected devices and digital services.

Samsung appears to understand perfectly that the value will not lie solely in the robot itself, but in the entire range of technologies that will allow it to operate, learn, communicate and interact with its surroundings.

The South Korean group is moving forward without major publicity, remaining faithful to an industrial strategy that favours long-term investment over spectacular demonstrations. Yet behind this discretion lies a considerable ambition: to make robotics the next stage of personal computing.

Should this vision become a reality, Samsung may no longer be known only as one of the world’s leading electronics companies. It could become one of the architects of the intelligent robotics systems that will accompany us in our everyday lives over the coming decades.

Cet article What Is Samsung’s Robotics Strategy? est apparu en premier sur Robot Magazine.

Unlike automated guided vehicles (AGVs), which follow predefined routes, AMRs analyze their environment in real time using a combination of LiDAR sensors, cameras, artificial intelligence, and simultaneous localization and mapping (SLAM) algorithms. This autonomy allows them to instantly adjust their route, avoid obstacles, and collaborate with operators without requiring major infrastructure modifications.

The market is currently experiencing sustained growth, driven by the expansion of e-commerce, smart factories, and Industry 4.0 strategies. Manufacturers are now competing to develop increasingly innovative robots that are faster, smarter, and capable of transporting heavier loads.

The Criteria That Distinguish the Best AMRs

Although performance is improving rapidly, not all autonomous mobile robots are designed to meet the same industrial needs. Some focus on order picking in warehouses, while others are designed to supply production lines or transport particularly heavy pallets.

Navigation quality naturally remains one of the primary selection criteria. Mapping accuracy, dynamic obstacle detection, and the ability to operate safely in environments shared with human operators directly determine the solution’s performance.

The centralized management of several dozen, or even several hundred, robots is also becoming a decisive factor for large industrial sites. The same applies to the ease of integration with warehouse management systems (WMS), manufacturing execution systems (MES), and enterprise resource planning (ERP) platforms.

AMRs do more than move goods.
They redefine the movement of
industrial flows.

Fifteen Manufacturers Shaping the Market

Among the most recognized players is MiR (Mobile Industrial Robots), whose collaborative mobile platforms have become a benchmark in European factories. Their ease of deployment and reliability explain their adoption across numerous industries, from automotive manufacturing to pharmaceuticals.

OTTO Motors, meanwhile, has established itself as one of the leading specialists in heavy-duty industrial applications. Its robots are particularly valued in manufacturing plants, where they automate the transportation of components between different production cells.

Acquired by Zebra Technologies, Fetch Robotics continues to equip numerous logistics warehouses. Its solutions are widely used to reduce unnecessary travel by order pickers and improve order preparation rates.

In Asia, Geek+ has become one of the global leaders in logistics robotics. The company deploys thousands of robots in major distribution centers, where they automate both storage operations and order preparation.

Locus Robotics follows a similar approach, with robots designed to assist operators rather than replace them. This human-machine collaboration significantly increases productivity while reducing the physical strain associated with repetitive tasks.

Major industrial robotics companies are also developing their own mobile platforms. Omron, ABB, KUKA, and Stäubli now offer AMRs that can be directly integrated into their automation ecosystems, creating continuity between fixed robots, production lines, and autonomous material-handling solutions.

Other specialized companies, such as SEER Robotics, ForwardX Robotics, SAFELOG, and AutoGuide Mobile Robots, focus on open architectures and highly flexible software to meet the specific requirements of systems integrators.

Finally, Toyota Material Handling continues to integrate mobile robotics into its logistics portfolio, while Mujin combines artificial intelligence, industrial vision, and mobile robotics to automate increasingly complex operations within next-generation warehouses.

The intelligence of an AMR is not measured
by its speed, but by its ability to make
the right decisions in real time.

A Technology at the Heart of the Smart Factory

Beyond the simple automation of internal transportation, autonomous mobile robots are gradually becoming intelligent platforms capable of interacting with the entire industrial ecosystem.

Advances in artificial intelligence now make it possible to optimize missions according to workload, battery levels, production priorities, and the movement of operators throughout the facility.

Future developments will also focus on coordinating fleets of several hundred robots, implementing predictive maintenance through the analysis of onboard data, and connecting AMRs with collaborative robots, robotic arms, and, in the longer term, humanoid robots designed for industrial environments.

Autonomous mobile robots are no longer an emerging technology, but a genuine driver of competitiveness. Their ability to automate logistics flows with flexibility, speed, and safety directly addresses the challenges faced by industrial companies around the world.

Although the choice of an AMR will always depend on the intended application, one trend is becoming increasingly clear: companies are now seeking scalable solutions that can be easily integrated into increasingly connected digital environments.

As artificial intelligence continues to enhance their decision-making and navigation capabilities, AMRs are expected to play a central role in the factories and warehouses of the next decade.

Cet article Top 15 Autonomous Mobile Robots (AMRs): The Leaders in Industrial Automation est apparu en premier sur Robot Magazine.