According to several industry estimates, the global humanoid robot market could reach between $30 billion and $60 billion by 2035, with annual growth exceeding 35%. Yet today, less than 1% of industrial companies use humanoids in real production environments. The gap between potential and adoption is telling.

From Technical Demonstration to Industrial Reality

Recent advances in robotics, driven by artificial intelligence and imitation learning, have made it possible to cross a major threshold. In 2025, several prototypes capable of performing picking or assembly tasks were unveiled. In 2026, some manufacturers are announcing tests involving fleets of 10 to 100 robots in controlled environments.

But those figures remain marginal. For comparison, a single automotive plant can deploy more than 1,000 traditional industrial robots.

The transition toward mass adoption involves challenges of a completely different nature:

• System standardization
• Large-scale maintenance
• Software interoperability
• Total cost of ownership (TCO)

Today, the cost of a humanoid robot still ranges between $50,000 and $150,000, which significantly limits large-scale deployment.

The real challenge is no longer
making a robot walk, but making
it work at scale.

We are no longer selling machines,
but ecosystems where hardware is
only the visible part of the data layer.

A Redefinition of the Robotics Model

The traditional robotics framework is evolving toward a systemic approach. In 2026, the most advanced players are no longer selling robots alone, but complete solutions integrating:

• Hardware
• Software
• Infrastructure
• Services
• Data

There is a clear convergence with SaaS models, where value shifts toward operations and data management.

Humanoid robotics is entering a new phase. After the era of technological innovation (2015–2025), the decade 2025–2035 will be defined by large-scale deployment.

The bottleneck has shifted toward infrastructure, regulation, and market integration. The companies that will dominate this market will not simply be those designing the most advanced robots, but those capable of deploying them at scale in real-world environments.

The next revolution will not be technological. It will be operational.

FAQ – The Challenges of Industrial-Scale Deployment

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A technical comparison at the heart of processors and protocols.

Rockwell Automation: The Strength of “Logix” and EtherNet/IP

The Milwaukee giant is built on one philosophy: The Connected Enterprise. Rockwell’s architecture is centered on the Logix controller family (ControlLogix and CompactLogix) and the Studio 5000 development environment.

Technical DNA:

Core protocol: Everything is built around EtherNet/IP. Unlike others that rely on proprietary layers, Rockwell uses CIP (Common Industrial Protocol) over standard Ethernet. This makes integration with enterprise IT layers easier, with Cisco as a long-time partner.

Programming philosophy: The approach is tag-based. Engineers do not manipulate raw memory addresses, but named variables directly at the firmware level.

Strengths: Exceptional native integration between drives (PowerFlex), HMIs (FactoryTalk), and PLCs. It is the “Apple” of industry: a closed ecosystem, but one that runs with remarkable smoothness.

Robot Magazine verdict: Ideal for large-scale process projects and heavy industry, where maintenance must be simplified as much as possible.

Automation is no longer a
hardware choice, it is a
20-year strategy.

Schneider Electric: EcoStruxure and Universal Openness

Schneider Electric has undergone a spectacular transformation, moving from a hardware manufacturer to a leader in industrial software. Its EcoStruxure architecture positions itself as the most open on the market, relying heavily on international standards.

Technical DNA:

Software convergence: With the acquisition of AVEVA, Schneider offers full digital continuity, from sensor to cloud. The PLC (M580 or M262) is no longer more than a node in a broader information network.

IEC 61499 innovation: Schneider is at the forefront of the IEC 61499 standard through EcoStruxure Automation Expert. Unlike the classic IEC 61131 standard, which is cyclical, IEC 61499 is event-driven and allows intelligence to be distributed: a block of code can run equally well in a speed drive or in the central PLC.

Strengths: Unmatched energy management. It is the architecture of choice for smart factories seeking to correlate power consumption with productivity.

Robot Magazine verdict: The most mature solution for those who want to break down silos between pure automation and data management (Big Data/AI).

Beckhoff: The PC-Based Revolution and the Power of EtherCAT

While Rockwell and Schneider are evolving the traditional PLC, German company Beckhoff has essentially eliminated it and replaced it with an industrial PC (IPC).

Technical DNA:

TwinCAT: The core of the system. It is a software platform that transforms a Windows kernel into a hard real-time operating system. It uses the computing power of Intel and AMD processors to drive ultra-complex machines.

Master of EtherCAT: Beckhoff invented EtherCAT, the fastest fieldbus in the world. Unlike EtherNet/IP, which sends individual packets, EtherCAT reads and writes data on the fly within a single frame that passes through all modules. The result: cycle times below 100 microseconds.

IT/OT integration: Beckhoff pioneered the use of C++ and C# directly in industrial control, alongside traditional Ladder Logic and Structured Text.

Robot Magazine verdict: The ultimate weapon for precision robotics, high-speed packaging, and special-purpose machines requiring intensive mathematical computation.

Topology Comparison: A Clash of Cultures

In Industry 4.0, software is
the new master of the
forge.

In-Depth Analysis: The Performance Duel

Motion control

In robotics, Beckhoff remains one step ahead thanks to EtherCAT. The synchronization of hundreds of axes happens with no perceptible latency. However, Rockwell has responded with its intelligent transport technologies, such as iTRAK, offering simplified mechanical and electronic integration for next-generation conveyor systems. Schneider, for its part, stands out with its Lexium range and its ability to integrate Delta or articulated robots through rich software libraries.

Cybersecurity: a critical challenge

Rockwell and Schneider have both adopted IEC 62443-4-2 certification, integrating security chips such as Secure Boot directly into their CPUs. Schneider emphasizes traffic transparency through integrated firewalls, while Rockwell focuses on granular access-right management via FactoryTalk Security. Beckhoff, by using Windows as its foundation, benefits from global security updates but requires deeper IT expertise to secure the operating system properly.

Which architecture for which future?

The choice between these three giants depends on your industrial legacy and your technological ambitions:

Choose Rockwell if you operate in North America or if you need a standardized architecture that is easy to troubleshoot by technicians familiar with clear and powerful logic systems.

Choose Schneider Electric if your priority is energy transition, software openness, and the desire to deploy a decentralized and agile architecture based on IEC 61499.

Choose Beckhoff if you are pushing the limits of physics: extreme cycle rates, complex machine vision integration, or the need to merge high-level software code with industrial automation.

In the era of software-defined manufacturing, the boundary between these players is becoming thinner, but their architectural philosophies remain essential compasses for the engineers of tomorrow.

FAQ – The Keys to Industrial Automation and IoT

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The main driver remains manufacturing: automotive, electronics, assembly, subcontracting. In this type of ecosystem, robotics scales quickly because the use cases are clear: welding, handling, vision, quality control, intralogistics.

But another key strength is the gradual structuring of an R&D backbone: laboratories and national programs that strengthen applied AI and autonomous systems. Hungary notably has an Artificial Intelligence National Laboratory (MILAB) (implementation period until February 2026) and coordinated efforts around autonomous systems.

A “hands-on” ecosystem: integrators, robotic cells, automation

As in most industrial markets, value is largely concentrated among:

• Integrators (cells, lines, retrofits)

• Automation companies (PLC, motion, vision)

• Robot training and maintenance centers

Concrete example: Robot-X (Hungary) positions itself in the design and construction of robotic cells, assembly lines, and special-purpose machines exactly the kind of player that drives the local market day to day.

Another example: Gamma Digital reports industrial integration and automation activities based in Budapest.

At the same time, major global suppliers continue to structure demand in industrial and intralogistics robotics (FANUC, KUKA, etc.), while mobile robotics / AMRs are growing strongly through intralogistics.

Hungary is betting on execution:
real robots doing real work, not
just ideas.

Research & talent: the key role of SZTAKI, MILAB, and universities

On the research side, one name comes up frequently: HUN-REN SZTAKI, highly visible in autonomy, control, drones, and cyber-physical systems. Its projects related to autonomous systems (road vehicles, drones, robots, manufacturing) clearly illustrate the country’s positioning on AI that interacts with the real world.

On the university front, Budapest concentrates active robotics teams (navigation, mapping, computer vision, control, multi-robot systems), notably at BME (Budapest University of Technology and Economics).

At ELTE, research groups report work on cognitive robotics, human–robot interaction, autonomous UAVs, and locomotion.

Focus: Allonic, the startup tackling the “robot body” bottleneck

The problem: AI is advancing faster than hardware industrialization
The robotics sector faces a tension: AI keeps improving, but manufacturing complex robots (and producing them at scale) remains slow and expensive. The bottleneck often lies in assembly, prototype iteration, and reproducibility.

Allonic’s approach: “3D Tissue Braiding”
Allonic claims to be developing a manufacturing method called “3D Tissue Braiding” to produce complex robotic structures, reducing assembly steps and accelerating iteration.

A market signal: a record fundraising
On February 10, 2026, several European tech media outlets reported a $7.2M pre-seed round led by Visionaries Club, presented as a record for Hungary, with participation from angels connected to the AI ecosystem.

Why this matters for Hungary

• Credibility: attracting investors of this caliber in deeptech hardware validates the country as a robotics base.

• Spillover effect: more talent, suppliers, and “robotics-first” projects.

• Positioning: instead of building “yet another AI app,” Allonic focuses on a core building block how robots are manufactured.

Hungary may not be the loudest market, but it is a very concrete one: an industry that automates, strong integrators, R&D hubs in AI and autonomy, and now a new deeptech wave embodied by Allonic. For European players, this is an ecosystem to watch and potentially a future Central & Eastern Europe hub for industrializing robotics building blocks.

Are you a robotics/AI player active in Hungary (startup, integrator, lab)? Contact Robot Magazine to be featured in our mapping and European dossiers.

Bonus: Spotlight on 20 Hungarian players (robotics + AI)

Startups / “Robotics & autonomy” tech

• Allonic – robot manufacturing platform, “3D Tissue Braiding,” $7.2M raised (2026).

• aiMotive – AI solutions and tooling for automated driving (Budapest), acquired by Stellantis (2022).

• ABZ Innovation – heavy-duty agricultural/industrial drones, funding announced January 2026.

• Advanced Robotics (HU) – robotics + AI integration/implementation for logistics and warehouses.

• OptoForce – force/torque sensors (Hungarian origin), technology integrated via OnRobot.

Integrators / industrial automation

• Robot-X Hungary Kft. – design and construction of robotic cells, assembly lines, special-purpose machines.

• Gamma Digital – industrial integration and automation (Budapest).

• B&O Engineering (B&O Kft.) – automation solutions / robotic cells (collaborative robots, accessories, multi-brand).

From startups to national laboratories,
Hungary is structuring the robotics
of the future.

Research / national programs

• HUN-REN SZTAKI – research in control, autonomy, cyber-physical systems, robots/drones.

• National Laboratory for Autonomous Systems – national coordination and communication around autonomous systems.

• MILAB (Artificial Intelligence National Laboratory) – national AI program (implementation until February 2026).

• BME (Budapest University of Technology and Economics) – Embedded Systems & Robotics: navigation, mapping, computer vision, robot manipulators.

• ELTE – Artificial Intelligence & Robotics Research Group: cognitive robotics, HRI, locomotion, UAVs.

Communities / federations

• Hungarian Robotics Association (ROBOHUN) – federation/community linking industry, education, and research.

• Hungarian Robot Builders Association – maker and robot-builder community (meetups, projects).

Major industrial players & suppliers present (energizing the market)

• FANUC (EU presence + local network) – industrial robotics and automation (major reference).

• KUKA Hungary – industrial robotics & Industry 4.0 (local presence).

• Bosch Rexroth Hungary – automation + mobile robotics / intralogistics (AMRs).

• Knorr-Bremse (Budapest) – R&D projects and communications around automation, robotic cells, and AI.

• Bosch / AI ecosystem in Hungary (e.g., collaborations with ELTE) – industry–research links around autonomous systems and AI.

FAQ – Robotics and AI in Hungary: Focus on Allonic and the Local Ecosystem

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To understand the genesis of RobotShop, you need to go back to my past as a combat engineer in the Canadian Army. During a mission in the former Yugoslavia, I faced the terrifying reality of landmines. Enemy technology was evolving rapidly metal, light, vibration, pressure, and pressure-release sensors while we were still often clearing mines lying on the ground with just a bayonet. I remember thinking: “I need to get out of here before I lose my life.”

After leaving the army, I pursued studies in robotics engineering, keeping in mind the idea of creating swarms of small “kamikaze” robots for humanitarian demining. To learn and become an expert, I started building robots in my apartment.

My first prototype, in the early 2000s, wasn’t a deminer it was a “Cat Hunter”! Imagine a chassis made from a tackle box, BBQ wheels, a thermal sensor salvaged from a garage light, glued onto a stepper motor recovered from a printer that served as the tracking head. I even rigged a tactile bumper using a copper tube and a piezoelectric component taken from an old speaker to detect obstacles, all controlled by a microcontroller programmed in BASIC. The robot worked so well it relentlessly chased my cat I had to deactivate it to preserve the animal’s sanity (laughs)!

But this “Maker” experience, building robots constantly, revealed a real problem: sourcing parts was a logistical nightmare. Every component had to be ordered from different places around the world. I realized that for robotics to advance, creators needed a centralized source. RobotShop was born from this frustration: creating a single platform to make it easier for enthusiasts and engineers to build useful robots for the future.

How has RobotShop’s mission evolved as the robotics market matured, from education to industry?

At first, the non-industrial market was mainly education, research, and Makers, with a few domestic applications like robot vacuum cleaners. We liked to call ourselves “the Amazon of robotics,” a simple way to explain what we did. Our unofficial slogan was “robotics at your service,” meaning we wanted to bring robotics into people’s lives in a concrete and useful way.

Today, the sector has matured, and we’ve evolved with it. We are no longer just a robotics store; we’ve become a global platform offering robotic solutions. Our new slogan is: “Everything Robotics, infinite possibilities”.

We began offering commercial and professional solutions, supported by a growing network of integrators. From robot kits to humanoids, we offer it all, aiming to accelerate and expand our range. From discovering the right robotic solution to financing, deployment, support, maintenance, and purchase or rental that’s what RobotShop is becoming.

We also opened our first showroom in Mirabel, Canada, which is essentially a living lab where customers can visit us. We plan to replicate this physical presence extensively, not only in Canada but internationally.

Our ambition is to build a global ecosystem where any robotic project can come to life through RobotShop.

With your unique perspective, what does the market still underestimate most in robotics: technology, applications, or real adoption?

All of the above (laughs). Take, for example, how humanoid robots will arrive in real-world applications faster than people think. There is still a lot of skepticism, which I understand. People see videos of robots dancing or doing flips and ask: “Okay, but what’s the practical use?”

What is less visible are the exponential forces working behind the scenes. I’m talking about major advances in three areas that reinforce each other: artificial intelligence, GPU power, and mechatronics (the physical dexterity of robots). AI allows robots to understand, adapt, and reason. Next-gen GPUs enable ultra-fast real-time computation, even locally. And physically, robots are becoming more stable, fluid, and capable of manipulating their environment precisely.

The combination of these three factors is a complete game-changer.

Few people also realize that major automotive manufacturers are already involved. Several have signed agreements with humanoid robot companies to integrate them, in the short term, into their assembly lines. These same partnerships, backed by industrial power, will enable mass production. We are no longer talking about lab prototypes; we’re talking about general-purpose humanoid platforms capable of performing a wide range of tasks just like a human, and in some cases, better.

Security and data privacy issues? They will be addressed in parallel. There will be rapid iterations, updates, and standards emerging, as always with disruptive technologies.

The result is that when these robots are “good enough” to replace certain human tasks at scale, they will be produced, delivered, and deployed massively and very quickly. It won’t be a slow, gradual change; it will be a wave.

As with all major technological breakthroughs, we radically underestimate the adoption speed once everything aligns.

If you had to summarize in one sentence the mission you still pursue today with RobotShop, what would it be?

“Together, fostering a world full of robots that positively impacts our lives.”

FAQ – RobotShop and Innovative Robotics

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This year marks a clear break from that trajectory. In 2026, robotics is no longer advancing incrementally. It is changing scale.

This shift is not driven by a single breakthrough, but by the convergence of artificial intelligence, embedded computing, simulation, labor shortages, and platform standardization. Robotics is moving beyond factory cells and entering the real world warehouses, hospitals, farms, construction sites, and public spaces.

For Robot Magazine, 2026 stands out as a pivotal year, comparable to the rise of cloud computing in the 2010s or the smartphone revolution in the early 2000s.

A Technology Long Limited by Its Own Constraints

Until recently, most industrial robots operated under strict conditions:

• fixed environments

• repetitive tasks

• deterministic programming

• limited perception

• high integration costs

Robots excelled at repetition but struggled with variability. A change in lighting, object shape, workflow, or layout often required costly reprogramming or system downtime.

This rigidity kept robotics largely confined to large-scale manufacturing, particularly automotive and electronics. Small and medium-sized enterprises, logistics, healthcare, agriculture, and construction remained largely manual.

The promise of robotics was clear but its reach was narrow.

What is happening in robotics is not
a technological miracle, but the
convergence of AI, computing power,
economics, and real-world constraints.

Artificial Intelligence Turns Robots into Decision-Making Systems

The first driver behind robotics’ change of scale is the maturation of artificial intelligence.

Modern robots are no longer just executing predefined trajectories. They are increasingly capable of:

• perceiving complex environments

• interpreting visual and sensor data

• understanding high-level instructions

• planning actions dynamically

• adapting to uncertainty

Multimodal AI models combining vision, language, force feedback, and motion allow robots to reason within constraints. This does not mean robots “think” like humans, but they can now make context-aware decisions instead of blindly following scripts.

This shift transforms robots from automated machines into physical AI agents, capable of operating in environments that were previously considered too unpredictable.

Embedded Computing Redefines Autonomy

Equally important is the rise of high-performance embedded computing.

Thanks to new generations of processors and AI accelerators, robots can now perform complex inference directly on board. This enables:

• real-time perception and decision-making

• low-latency control loops

• reduced dependence on cloud connectivity

• improved reliability and safety

• better data sovereignty

Robots no longer need external PCs or centralized servers to function intelligently. They have become edge systems, capable of operating autonomously even in remote or critical environments.

This is a fundamental shift. Intelligence is no longer centralized it is distributed across fleets of machines.

Robots Enter Unstructured, Human-Centric Environments

Robotics is changing scale because robots are no longer designed only for structured spaces.

Alongside traditional industrial arms, we now see:

• autonomous mobile robots navigating busy warehouses

• collaborative robots working safely next to humans

• service robots operating in hospitals and hotels

• agricultural robots adapting to natural terrain

• inspection and maintenance robots in infrastructure

• humanoid robots designed for human-built environments

The defining feature of these robots is not their form factor, but their adaptability. They operate in spaces built for humans, not redesigned for machines.

This marks a major philosophical shift: instead of forcing the world to adapt to robots, robots are adapting to the world.

Labor Shortages Accelerate Adoption

Beyond technology, economics plays a decisive role.

Across industries and regions, companies face:

• aging workforces

• labor shortages in physically demanding jobs

• high turnover rates

• declining interest in repetitive or hazardous tasks

In logistics, agriculture, manufacturing, healthcare, and sanitation, automation is no longer about productivity alone. It is about operational continuity.

Robotics becomes a necessity rather than an optimization tool. In many cases, robots are not replacing workers they are filling positions that no longer attract human labor.

This structural shift is one of the strongest accelerators of large-scale robotic deployment.

Robotics may be less visible than
consumer AI, but its transformation
is deeper, slower and far more structural.

Platform Standardization Fuels the Ecosystem

Another key factor behind robotics’ change of scale is platform convergence.

The robotics sector has long been fragmented, with proprietary hardware, software, and integration methods. That fragmentation is now giving way to:

• shared operating systems and middleware

• common simulation and development tools

• standardized interfaces between robots and IT systems

• cloud-edge hybrid architectures

This standardization reduces development costs, shortens deployment cycles, and lowers barriers to entry for new players. It also allows skills, software, and best practices to transfer across platforms.

Robotics is beginning to resemble modern computing: modular, updateable, and ecosystem-driven.

From Individual Robots to Robotic Infrastructure

Perhaps the most important shift is conceptual.

Robots are no longer treated as isolated machines. Companies now think in terms of:

• robot fleets

• centralized supervision

• orchestration layers

• predictive maintenance

• digital twins

• continuous learning systems

A robot deployed today improves tomorrow through shared data, software updates, and collective learning across fleets. Value increasingly lies in software, data, and integration not just hardware.

Robotics is becoming an infrastructure layer, similar to IT systems or cloud platforms.

Challenges Remain and They Are Significant

Despite this change of scale, robotics still faces real obstacles:

• high upfront investment costs

• cybersecurity risks

• regulatory and safety compliance

• ethical and social concerns

• workforce adaptation and training

Technology is advancing faster than organizational readiness. Deployment success depends not only on engineering, but also on change management, regulation, and human acceptance.

The challenge is no longer whether robots can perform tasks but how societies and industries integrate them responsibly.

2026: A Pivotal Year

What makes this year different is not hype, but alignment.

Technology, economics, and societal needs are converging. Robotics is expanding beyond pilot projects and isolated use cases into scalable, repeatable deployments across sectors.

Manufacturing, logistics, healthcare, agriculture, energy, and public services are all being reshaped by robotic systems that are more autonomous, flexible, and intelligent than ever before.

This shift is irreversible.

A Quiet but Structural Transformation

Robotics may not dominate headlines like consumer AI, but its impact is deeper and more structural. The change of scale we are witnessing this year reflects the maturation of robotics as a foundational technology.

Robots are no longer futuristic promises. They are becoming reliable, adaptable tools embedded in everyday operations.

For Robot Magazine, 2026 marks the moment when robotics transitions from a specialized industrial solution to a cross-sector infrastructure, reshaping how work is performed, how services are delivered, and how physical systems interact with digital intelligence.

The key question is no longer if robotics will scale but how quickly industries and societies will adapt to this new reality.

FAQ – Why Robotics Is Changing Scale in 2026

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By unveiling its MOTOMAN NEXT platform, Yaskawa marks an important milestone in industrial automation. The Japanese company, already well established in robotics and automation, introduces an architecture designed to bridge two worlds long kept apart: traditional industrial automation (OT) and advanced digital technologies (IT).
The goal? To make robots capable not only of executing tasks, but also of observing, understanding, and adapting in a global context marked by labor shortages and the rise of complex tasks demanding automation.

An All-in-One Platform Unifying Hardware, Software, and Embedded Intelligence

According to the press release, MOTOMAN NEXT is presented as a complete solution in which “robot, controller, software, and engineering tools” are grouped into a single ecosystem.

The core of the system relies on two main units:

• RCU (Robot Control Unit): the traditional robot control unit.

• ACU (Autonomous Control Unit): a new module dedicated to intelligent functions, based on NVIDIA Jetson Orin NX-Edge, integrating CPU + GPU, running Linux with Docker support.

This hybrid architecture paves the way for robotics that depends less on external computers, by integrating directly into the controller functions usually assigned to IT stations: image processing, AI, vision, planning, sensor management…
A rare approach in an industry typically fragmented between PLC logic and PC-based software.

Yaskawa also provides pre-installed APIs for motion control, planning, 2D/3D vision, force control, and image processing via HALCON ©.

A ROS2 interface connected via gRPC further opens the platform to the open-source robotics community.

With MOTOMAN NEXT, Yaskawa is no
longer just programming robots: it is
teaching them to perceive, understand,
and adapt.

Toward a Fusion of OT and IT Worlds

A section of the press release highlights a major problem in modern industrial robotics: the gap between the languages, tools, and programming philosophies of OT engineers and IT developers.
OT engineers work with PLCs, while IT developers use high-level code (Python, C++), often generated on a PC then injected into the robot through interfaces that can be limited or prone to latency.

MOTOMAN NEXT attempts to bridge this gap by bringing these logics together in a single controller capable of executing standard Docker modules while optimizing classic industrial robotics functions (kinematics, speeds, singularities) for Yaskawa hardware.

This integration avoids historical issues such as:

• Complex waypoints
• Unstable dynamic behavior
• Dependency on external PCs
• Difficult integration of vision or sensors

The idea is to offer IT developers the experience of a seasoned robot programmer while ensuring that advanced applications vision, AI, perception run directly at the controller level.

Robots That Perceive, Understand, and Produce

This change of methodology is described as a transition from the paradigm “Code and produce” to “Perceive and produce”.

Traditional robots operate in deterministic environments, with standardized parts and preprogrammed sequences. But when variability increases formats, batch sizes, operation order classical programming reaches its limits.

With the combination of sensors + AI, MOTOMAN NEXT targets applications previously reserved for human workers:

• Flexible assembly
• Sorting and handling of unstructured flows
• Variable loading/unloading
• Random cleaning and manipulation
• Harvesting and packaging in changing environments

Potentially impacted sectors go far beyond heavy industry: logistics, healthcare, construction, food service, recycling all industries currently suffering from labor shortages.

A New Line of Industrial Robots and Cobots

The MOTOMAN NEXT line NEX series covers payloads from 4 kg to 35 kg, with high-inertia servomotors designed to ensure perfect alignment between the digital model and real operation, facilitating simulation and virtual optimization.

Yaskawa also introduces new cobots (NHC series: 12 and 30 kg), equipped with an embedded RGB-D camera enabling direct perception from the robot and adaptive reactions in real time.
This “bodycam” opens the door to more natural interactions between robot and environment.

Digital Twin and Advanced Engineering

The MOTOMAN NEXT package includes the YNX Robot Simulator, a professional simulation tool enabling:

• Virtual cell creation
• Trajectory testing
• AI scenario validation
• Optimization before real deployment

This digital twin is key to reducing development risks and supporting the industrialization of intelligent robotic applications.

For advanced teams, Yaskawa also announces official support for NVIDIA’s tools: Isaac Sim and Cumotion.

Robotic autonomy is entering a new era
where the robot is no longer dependent
on an external PC to think.

A Simplified Operator Interface

On the operator side, Yaskawa focuses on continuity: the Android Smart Pendant tablet remains the main interface. Sequences can be created in block-based language using icons representing functions (planning, vision recognition…), making programming more intuitive.

The platform is also prepared for next-gen LLM-based interactions: voice commands, gestures, AR (augmented reality) assistance.

Automatic Trajectory Planning: A Key Feature

Among the highlighted technical features, automatic collision-free trajectory planning (Path Planning) plays a central role.
A simple “MOVAUTO” command would allow the robot to move from point A to point B while automatically avoiding surrounding obstacles.

This planning relies on 3D modeling:

• Static: cell model
• Dynamic: real-time updates from the camera

This is essential for AI applications and evolving Industry 4.0 environments.

A Strategy Based on Partnerships and Real-World Use Cases

Yaskawa emphasizes that the success of AI/robotics projects depends on close cooperation between:

• End users
• Integrators
• Technology partners
• Yaskawa

The goal is to go beyond prototypes and achieve solutions that are fully industrialized and capable of continuous production.

A Significant Breakthrough in a Changing Robotics Landscape

With MOTOMAN NEXT, Yaskawa is not simply launching a new robot line: it is proposing a complete re-architecture of the robotics development cycle.
The OT/IT fusion, native integration of AI and vision, advanced simulation, embedded perception, and intelligent planning address today’s challenges: automating complex tasks, making robots more autonomous, and compensating for labor shortages across many sectors.

If the platform delivers on its promises in real-world deployments, it could redefine industrial robotics standards where the boundary between mechanical execution and software intelligence is progressively disappearing.

FAQ – Yaskawa MOTOMAN NEXT

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A Long Reach in a Slimmer, Lighter Form Factor

Retaining the 1,750 mm reach of the UR20, the UR8 Long stands out with a slimmer profile and lighter architecture. It delivers a payload capacity of 8 kg, suitable for precision tasks such as inspection, handling, and welding.

Its compact and robust design targets factories where footprint is limited particularly in metal fabrication, automotive, and plastics industries. Weighing roughly 70% of the UR20, and equipped with a more compact wrist, the cobot is easier to install on gantries, rails, and other external axes.

The real revolution is not in the
robot that walks, but in its ability
to transform human labor.

A Cobot Engineered for Complex Welding

Universal Robots clearly positions the UR8 Long as a response to the growing demand for collaborative welding.
The extended reach, combined with UR’s new MotionPlus technology, enables smoother trajectories and consistent quality, even on large or irregular assemblies. High repeatability and fine motion control are intended to reduce finishing work, such as grinding and rework.

For many companies, the introduction of collaborative welding solutions is also a way to attract younger talent, often more motivated by robot-assisted work than by traditional manual welding, which remains physically demanding and difficult to staff.

Partnership demos at FABTECH including THG Automation, Hirebotics, and Vectis Automation illustrate the ecosystem forming around the new model.

Enhanced Bin Picking Capabilities

Beyond welding, the UR8 Long targets another increasingly strategic use case: bin picking.
The combination of long reach, compact wrist, and faster joint speed allows the cobot to access deeper areas of industrial bins common in automotive, metalworking, and manufacturing.

According to UR, improvements in joint design can reduce cycle times by up to 30% compared to previous-generation cobots, an important factor in high-throughput environments.

Intuitive Programming With PolyScope 5 and PolyScope X

The UR8 Long operates with UR’s PolyScope 5 and PolyScope X platforms.
The updated Freedrive mode enables more precise, manual path teaching by simply guiding the arm by hand no external software or hardware tools required.

MotionPlus improves synchronisation with linear axes, rotary tables, and positioners, enabling smoother, more accurate complex motions in multi-axis automated cells.

With the UR8 Long, Universal Robots
aims to combine long reach and compactness
two features rarely found together in
industrial workshops.

European Demonstrations to Follow

After its debut in Chicago, the UR8 Long will be showcased in Europe on 18 September at SCHWEISSEN & SCHNEIDEN in Essen, Germany. A first demonstration in France is scheduled for 18 November at the Prod&Pack trade show in Lyon.

A Step Forward in UR’s “Automation for Everyone” Strategy

The UR8 Long fits within Universal Robots’ stated goal of making automation accessible to businesses of all sizes. With over 100,000 cobots deployed worldwide and a strong ecosystem of software, training, and integration partners, the company continues to push collaborative robotics into tasks that were traditionally reserved for conventional industrial robots.

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Today, whether it’s industrial robots, autonomous vehicles, drones, humanoid robots, or intelligent logistics systems, NVIDIA is everywhere. This dominance is not built on a single product, but on a coherent, integrated, and deeply industrialized ecosystem: Jetson, Isaac, and Omniverse.

This investigation deciphers how NVIDIA has managed to build the world’s most complete platform to design, train, simulate, and deploy intelligent robots at scale and why this strategy places it at the heart of the next industrial revolution.

Robotics enters the era of native AI

Robotics is undergoing a structural transformation. Robots are no longer programmed solely through deterministic rules. They are becoming:

• Perceptive (2D/3D vision, LiDAR, audio)

• Adaptive (continuous learning)

• Autonomous (decision-making in complex environments)

• Connected (edge, cloud, digital twins)

This transformation relies on a key condition: embedded computing power capable of running advanced AI models in real time, while remaining energy-efficient, robust, and industrially deployable.

This is precisely where NVIDIA has taken a decisive lead.

Jetson: the embedded brain of modern robotics

The NVIDIA Jetson range is now the de facto standard for embedded AI in robotics.

Jetson is not just a hardware module. It is a complete platform combining:

• NVIDIA GPUs optimized for AI

• High-performance ARM CPUs

• Dedicated accelerators (Tensor Cores)

• Native support for AI frameworks (CUDA, TensorRT, PyTorch)

• Controlled power consumption

Modules like Jetson Orin can now run simultaneously:

• Computer vision

• SLAM

• Object detection

• Trajectory planning

• Multimodal inference

• Cloud–edge communication

All of this directly on the robot, without permanent reliance on the cloud.

As a result, Jetson powers a vast diversity of systems:
industrial robots, AMRs, agricultural robots, drones, medical robots, humanoids, security robots, and autonomous vehicles.

Jetson has become the “universal brain” of AI-driven robotics.

Isaac: the framework that structures robotic intelligence

If Jetson is the brain, NVIDIA Isaac is the nervous system.

Isaac is a comprehensive software suite dedicated to robotics, designed to work end to end from development to production.

It includes:

• Isaac ROS: native integration with ROS 2, GPU-accelerated

• Isaac Sim: a photorealistic simulation environment

• Perception, manipulation, and navigation libraries

• Reinforcement learning pipelines

• Pre-trained models for robotics

Isaac addresses a central problem in modern robotics: software fragmentation.
Where teams once spent months assembling heterogeneous components, NVIDIA now offers a coherent, hardware-accelerated, and industrial-grade stack.

Isaac ROS, in particular, marks a turning point. It enables ROS nodes to run directly on the GPU, dramatically improving:

• Latency

• Accuracy

• Robustness

• The ability to process complex sensor streams

Omniverse: simulation as a strategic weapon

With Omniverse, NVIDIA changes scale entirely.

Omniverse is not just a simulation tool. It is a collaborative platform for industrial digital twins, built on USD (Universal Scene Description), which has become central to the industry.

For robotics, Omniverse enables:

• Creation of photorealistic environments

• Simulation of thousands of scenarios simultaneously

• Large-scale reinforcement learning training

• Testing of dangerous or rare behaviors

• Connecting simulation and the real world (sim-to-real)

Thanks to Omniverse, robots can learn before they even physically exist.

In automated warehouses, factories, ports, power plants, or smart cities, Omniverse becomes a permanent digital laboratory.

Jetson + Isaac + Omniverse: a closed-loop robotic AI system

NVIDIA’s strength lies in the total integration of these three pillars:

• Omniverse to simulate and train

• Isaac to structure intelligence

• Jetson to execute AI in real-world conditions

This closed loop enables:

• Massive cloud-based training

• Validation via digital twins

• Optimized deployment on real robots

• Field data collection

• Continuous model improvement

Very few players worldwide master this entire chain.

Why NVIDIA is ahead of Google, Microsoft, and Tesla in robotic AI

Each tech giant has a specific strength:

• Google excels in theoretical AI and perception

• Microsoft dominates industrial cloud and orchestration

• Tesla innovates through extreme vertical integration

• Amazon focuses on logistics robotics

But NVIDIA stands out with a unique position:
the convergence point between hardware, AI, simulation, and robotics.

Three key advantages explain this dominance:

1. NVIDIA controls computation
   Robotic AI is computationally intensive. NVIDIA provides GPUs, edge AI, accelerators, frameworks, and low-level optimizations.

2. NVIDIA is manufacturer-neutral
   Unlike Tesla, NVIDIA does not build its own robots. It equips everyone from startups to industrial giants.

3. NVIDIA has industrialized simulation
   Where simulation was once an R&D tool, NVIDIA has made it an industrial pillar.

Humanoids, autonomous vehicles, and general-purpose robots

The Jetson–Isaac–Omniverse ecosystem is now at the core of the most ambitious projects:

• Industrial humanoid robots

• Autonomous vehicles

• General-purpose, multi-task robots

• Military and security systems

• Advanced collaborative robots

NVIDIA is actively working on foundation models for robotics, capable of transferring skills across tasks, environments, and platforms.

The vision is clear: create a universal robotic intelligence, adaptable to any mechanical body.

Toward a global standard for robotic AI

As the NVIDIA ecosystem gains traction, one question emerges:
Is Jetson–Isaac–Omniverse becoming the global standard for robotic AI?

More and more signals point in that direction:

• Massive industrial adoption

• Native integration with ROS 2

• Cloud compatibility (Azure, AWS, GCP)

• Strong developer support

• A clear roadmap toward generative robotic AI

In the long term, NVIDIA could play for robotics the role Intel once played for PCs but with a far broader and more systemic ambition.

NVIDIA, the silent architect of the robotics of the future

NVIDIA does not merely accompany the robotic revolution.
It is designing its deep architecture.

By simultaneously mastering:

• Computation

• AI

• Simulation

• Embedded deployment

NVIDIA establishes itself as the central player in global robotic AI.

In the coming years, most intelligent robots will not function solely thanks to algorithms, but thanks to an invisible, standardized, and optimized infrastructure.

And that infrastructure already has a name: NVIDIA.

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The sheet metal industry is undergoing a profound transformation thanks to robotic automation, and one of the highlights of this evolution is the Configurable Robotic Bending System (RBS) recently showcased by LVD. As reported by Canadian Metalworking, this system provides metal fabrication shops with unprecedented flexibility by allowing them to customize their robotic bending cell according to their precise needs.

In this article, we will explore what the RBS is, its main benefits, technical features, typical use cases, and points of caution. We will conclude with a FAQ addressing the most common questions.

1. What is the configurable Robotic bending system?

The LVD RBS (Robotic Bending System) is a modular automation platform that combines a press brake, a robotic manipulator, software, and grippers tailored to the user’s requirements.

Unlike rigid “turnkey” cells, the RBS allows multiple parameters to be configured:

• Choice of press brake (force, length, type)

• Type of material input and output (bins, pallets, conveyors)

• Style of robotic gripper depending on the weight, material, and geometry of parts

The goal is to ensure that each cell is perfectly adapted to a shop’s production flow, maximizing productivity while optimizing return on investment.

2. The three RBS platforms

LVD offers the RBS in three platforms, depending on the size and weight of the parts to be bent:

• RBS 4: for light parts up to 4 kg, maximum dimensions approximately 600 × 400 mm. Compatible with 40–50 ton presses.

• RBS 40: capacity up to 40 kg, larger parts (1600 × 1200 mm), profiles up to 2000 mm. Presses from 80 to 220 tons.

• RBS 80: for very large parts, up to 80 kg, profiles up to 3000 mm, and high-force presses (135–220 tons).

This modularity allows companies to select the platform that matches their production needs without paying for features they won’t use.

3. Technical features and innovations

Key highlights of the RBS include:

• Offline programming software
  LVD’s CADMAN-SIM software automatically generates robot trajectories and bending sequences without requiring on-machine training.

• Intuitive interface
  The system is controlled via a “Touch-B” touchscreen that manages both the press and the robot, simplifying operations.

• Adaptive bending (optional)
  With the Easy-Form® Laser system, the RBS can measure bending angles in real time and automatically adjust to compensate for thickness variations, work hardening, or grain direction.

• Manual operation possible
  The press can be used in manual mode if needed, useful for small batches or one-off parts.

• Variety of grippers
  Users can choose from different types of grippers: universal, magnetic, heavy-duty, etc., depending on the nature of the parts.

• Configurable material flow
  Input/output options include feed bins, pallets, and conveyors, allowing optimization of production flow.

4. Benefits of flexible automation

The RBS system offers several major advantages:

• Production flexibility: By configuring the cell to their needs, shops can handle varied batches, from small runs to medium volumes, without unnecessary costs.

• Reduced cycle time: Automatic programming and tight robot-press coordination minimize downtime.

• Improved quality: Adaptive bending ensures precise angles from the first bend, reducing scrap.

• Rapid return on investment: Precisely adapting the cell avoids overspending, accelerating ROI.

• Scalability: The system can evolve with future needs (changing press, gripper, or flow) thanks to its modularity.

5. Typical applications

The LVD RBS is particularly useful in:

• Metal fabrication shops with a wide range of parts from small, lightweight components to larger, heavier pieces.

• Companies aiming to automate while retaining production flexibility, especially when alternating between manual and robotic production.

• Manufacturers seeking consistent quality and minimizing manual adjustments.

• Firms looking to industrialize without overinvesting, building a tailored cell rather than an oversized “just-in-case” system.

6. Points of caution

Although the RBS is very powerful, certain aspects should be considered before adoption:

• Initial cost – Even configurable, a robotic system requires a significant investment (robot, press, software, integration).

• Training & maintenance – Operators need training on the press, robot, and simulation software.

• Floor space – Depending on the chosen configuration (input, output, press type), the cell can occupy significant workshop space.

• Advanced customization – Excessive customization can complicate maintenance if specific parts (grippers, stations) are used.

• Robotic safety – Like any robotic system, safety measures (sensors, barriers if needed) are required to protect operators.

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While most global robotics giants compete through flashy communication and loud innovation, Japan continues to follow its own path: one of discretion, reliability, and functional perfection. No bold slogans or spectacular product launches here. Japanese industrial robot manufacturers prefer to let their machines speak for themselves often recognizable by their minimalist design and micron-level precision.

This philosophy is rooted in a simple conviction: the quality of a robot is not measured by its appearance, but by its ability to operate continuously, day and night, for years. This rigor, inherited from monozukuri the Japanese art of demanding, meticulous manufacturing has shaped the foundations of Japanese robotics.

Total Control Over the Industrial Chain

The secret behind the Japanese model lies in its complete mastery of the manufacturing process. Some companies produce nearly all their own components: motors, servomotors, electronic boards, CNC software even the robots used to build other robots.

This level of integration is rare. It enables absolute quality control, perfect software consistency, and simplified maintenance. In the world of industrial robotics where axis precision is measured in microns and repeatability is essential this integrated approach becomes a strategic advantage.

The result: robots capable of performing millions of cycles without weakening, with one of the lowest failure rates in the industry.

The Cult of Reliability Above All

In Japanese factories, reliability is not a marketing claim  it is a core belief. Every robot and every CNC controller is subjected to extreme testing before shipment. Some systems are designed to operate continuously, 24/7, for decades.

This obsession with durability stems from a deeply rooted cultural principle: kaizen, continuous improvement. Each component, each line of code is refined over time not through dramatic revolutions, but through precise and relentless evolution.

It is this philosophy that allows some Japanese factories to operate for decades without direct human intervention, in a kind of almost poetic mechanical harmony.

The Autonomous Factory: A Dream Realized in Japan

Long before the term Industry 4.0 became fashionable, Japan was already experimenting with autonomous factories capable of operating in complete darkness the famous lights-out factories. These automated sites require no lighting because the robots do not need to see. They work without breaks, without fatigue, and without error.

These facilities embody the Japanese vision of automation: a factory where robots build other robots, maintained by self-diagnostic and predictive maintenance systems.

The goal is not to replace humans, but to free workers from repetitive tasks so they can focus on oversight, design, and continuous improvement.

Today, this model inspires manufacturers worldwide, especially in Europe, where productivity and quality goals often clash with labor and energy constraints.

The Perfect Symbiosis Between CNC and Robotics

Another pillar of the Japanese model is the fusion of CNC systems with robotics. In a Japanese factory, robots are not isolated machines. They are natural extensions of machine tools, sharing the same control logic, sensors, and precision.

This integration allows perfect synchronization between robotic movements and machining cycles, with fine control of feed rates, torque, trajectories, and positions.

The result: improved energy efficiency, drastically reduced error rates, and production with unmatched precision.

This union between CNC and robotics has made Japan a benchmark of excellence in industries where tolerances are extremely strict: microelectronics, medical devices, aerospace, and watchmaking.

A Human-Centered Philosophy

Despite the high level of automation, Japanese robotics never loses sight of its purpose: serving the human. Japanese engineers often speak of kokoro the “heart” or spirit infused into the creation process.

Behind each robotic arm is a clear intention: to design a tool that is reliable, safe, and beneficial to society.

Instead of seeing automation as a threat to employment, Japan sees it as a natural extension of human skill. The robot becomes a partner a continuation of the human gesture, a tangible expression of collective technical mastery.

This cultural dimension deeply differentiates the Japanese model from the Western one, which is often driven primarily by short-term profitability.

The Japanese Lesson for Global Industry

Faced with today’s challenges decarbonization, reshoring, and skilled labor shortages the Japanese model offers valuable inspiration.

It shows that it is possible to combine high technology, longevity, and respect for human work provided one adopts a systemic and patient approach.

European manufacturers are now trying to learn from it: unifying software platforms, internalizing critical components, and reducing dependence on subcontractors.

But reaching the level of industrial coherence that Japan has built over decades will take time.

Toward a New Era of Precision

As artificial intelligence and digital twins redefine production standards, Japan’s lessons resonate more strongly than ever.

The future of robotics will not be determined solely by speed or flexibility, but by stability, mastery, and reliability.

Japanese perfection is not spectacular. It is quiet, patient, and methodical.

And it is precisely this constancy that has inspired engineers around the world for more than half a century those who dream of machines that never stop, never fail, and embody the noblest promise of technology: absolute trust in the mechanical.

FAQ – The Japanese Philosophy of Industrial Robotics

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