The quiet rise of factory humanoids
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The quiet rise of factory humanoids
The next decade of robotics won’t be shaped by robots that backflip, but by the ones that can pick up tools, hit torque specs, and work safely beside humans.
Factories hum with the quiet tension of modern industry. Labor shortages are everywhere. Reshoring is bringing production back to facilities never designed for today’s automation. Precision is demanded, yet humans are stretched thin. In this context, a new generation of humanoid robots is quietly entering the industrial spotlight as practical solutions to real bottlenecks.
Matt Moseman of DEVELOP, a single-source automation integrator, cuts through the hype. “Humanoids are getting attention, but factories don’t buy robots because they look like people. They buy tools that solve bottlenecks. Right now, labor scarcity and reshoring are creating bottlenecks everywhere, which is why humanoids are finally getting their moment,” Moseman tells Interesting Engineering.
Humanoids are best suited to high-mix, low-volume work: aerospace subassemblies, automotive rework, and awkward material handling in older factories. Here, a human-shaped reach isn’t a gimmick, but a solution. Moseman emphasizes: “If a humanoid can hit cycle time and uptime targets on the boring stuff, then it earns the right to scale.”
Humanoids are best suited to high-mix, low-volume work: aerospace subassemblies, automotive rework, and awkward material handling in older factories. Here, a human-shaped reach isn’t a gimmick — it’s functional. “If a humanoid can hit cycle time and uptime targets on the boring stuff,” Moseman says, “then it earns the right to scale.”
Brendan Englot, associate professor of Mechanical Engineering at Stevens Institute of Technology, notes that humanoids serve a bridge role.
“They can have one foot in each of those worlds, allowing humanoids to take on the risk of working in close proximity to dangerous equipment and processes, while also being able to access the tools, equipment, and environments intended for humans. This has the potential to improve both safety and efficiency while the technology is still in its nascent stages.” Englot tells IE.
While humanoids can run, climb, and even perform acrobatics, many still cannot reliably pick up a screwdriver.
“Everything around us assumes human-level dexterity,” Mike Obolonskyi, principal at Cortical Ventures, explains. Door handles, socket wrenches, and factory machinery demand nuanced force, rotation, and grip. “Most economic value comes from manipulation, not mobility. Industries like manufacturing, assembly, and food preparation rely on physical work. Estimates place manual-labor compensation at around 50% of global GDP – roughly $42 trillion per year.” Obolonskyi explains.
Yet the industry has historically emphasized locomotion over dexterity. Tesla’s Optimus, Boston Dynamics’ humanoids, and others often showcase walking or stunts in demos, but these capabilities contribute little to productivity on the factory floor. The true challenge (and opportunity) lies in manipulation: the precise, context-aware interaction with the environment that humans perform effortlessly.
As Fernando Portela Cubillo, director of Future Technologies at Freudenberg Technology Innovation, explains, for humanoid robots to become mainstream in these environments, their joints, actuators, and internal systems must withstand high friction, heat, dust, vibration, chemicals, moisture, and constant motion.
“That requires high performance lubrication, compact, flexible and durable components like seals, elastomers and plastics – all types of components Freudenberg already provides to robotics manufacturers worldwide. This R&D is where Freudenberg’s focus lies today.
Over the next decade, we expect humanoid robots to become practical assistants in these industrial settings. Their progress will rely not only on advances in autonomy and AI, but heavily on their mechanical foundations that enable durability, safety and repeatable movements,” Cubillo tells IE.
The earliest adoption of humanoid robotics is already happening in industries with the most structured workflows and the most severe labor constraints – warehousing, logistics, and manufacturing, says Tyler Niday, CEO of Bonsai Robotics. “The pattern matches what we’ve seen in agriculture: our autonomy platform found traction first in operations where growers were struggling to hire crews or losing productivity due to labor gaps,” Niday points out.
The investment gap: Dexterity vs. mobility
However, one of the more surprising truths about humanoid robotics is how the flow of money has shaped the field. Over the past decade, billions have been poured into mobility – robots that walk, roll, or navigate autonomously – but far less has been invested in the very skills that actually generate economic value: dexterity and manipulation.
The numbers tell the story: autonomous vehicle technology alone has soaked up over $200 billion in investment since 2010. Meanwhile, companies focused on manipulation – Physical Intelligence, Skild AI, Covariant, Dexterity – have raised hundreds of millions combined, impressive but dwarfed in scale. The imbalance is striking, and it reflects a fundamental challenge: teaching a machine to move through space is far easier than teaching it to interact with the world as skillfully as a human hand.
Dexterity requires breakthroughs in compact actuators, tactile sensing, and AI that can reason across vision, touch, and language. Mobility can lean on mature sensors and fusion algorithms; manipulation has to reinvent the stack entirely. Yet this is where the real value lies, and where humanoids must prove their worth if they are to become more than curiosity-driven prototypes.
Brain-like intelligence at the edge
This is where neuromorphic computing and spiking neural networks (SNNs) come into play. Unlike conventional AI that relies on power-hungry cloud servers, SNNs mimic the human brain, processing sensory input in sparse, event-driven bursts.
Sumeet Kumar, CEO of Innatera, explains: “We set up the company to bring very efficient, brain-like AI directly to sensors so that we could process the world as soon as the data is captured at the source.” The company’s Pulsar chip embeds intelligence directly at the sensor, enabling real-time decision-making while drastically reducing energy consumption.
Compared to conventional neural networks, SNNs are 100 times smaller, more responsive, and extremely energy-efficient. This allows robots to handle microsecond-level decisions – like stopping a robotic arm if a human steps into its path – without relying on centralized computing.
The combination of humanoid robots and neuromorphic sensors has immediate industrial applications. A robotic arm equipped with Pulsar chips can adjust grip, posture, and force in real time, performing tasks that require precision and safety. High-mix, low-volume tasks – such as loading fixtures, torquing brackets, or handling fragile components – become feasible without human oversight at every step.
At the same time, humanoids are increasingly being designed for collaborative work, integrating seamlessly with human operators – an approach that allows humans and robots to complement each other, performing tasks aligned with their respective strengths. Additionally, there are also issues such as unreliable or unavailable GPS in complex industrial environments – warehouses, ports and logistics hubs – which prevent robots from navigating safely and autonomously.
This is precisely the problem that French startup Exwayz is tackling, aiming to free autonomous robotics from GPS constraints. As Exways’ CEO co-founder Hassan Bouchiba puts it, the next decades will see robots, humanoids included, transform factory work, but not by replacing humans.
“Humans will shift toward supervision, exception handling, quality control, and high-value decision-making, while robots take over physically demanding or monotonous tasks. We’re already seeing this shift through our customers. At the Port of Rotterdam, Embotech’s autonomous trucks powered by Exwayz SLAM show how mobile robots can assume heavy transport and logistics tasks that used to rely on human endurance. This example shows how humanoids will take on similarly challenging, mobile operations inside industrial facilities,” Bouchiba tells IE.
Edge AI and the sensor revolution
Kumar emphasizes the importance of processing data at the source: “By 2030, there will be around 63 billion active sensors generating data. Moving all that to the cloud is impossible – too slow, too costly, and too energy-intensive. Neuromorphic processing allows us to handle that data immediately, efficiently, and privately.”
Embedded intelligence enables robots to make split-second decisions in dynamic environments, ensuring both safety and efficiency. This capability is especially critical in factories with complex, fast-changing workflows.
The path forward for humanoids is deliberate. Narrow tasks first, then scale. Success depends on reliable performance, not media spectacle. Moseman emphasizes: “Humanoids will start quietly. If a robot can do the boring stuff reliably, that earns the trust of the floor.”
Obolonskyi adds that the industry must correct its historical priorities: dexterity and manipulation should take precedence over locomotion and stunts. Only then will humanoids unlock their full economic potential and contribute meaningfully to global productivity.
The convergence of industrial robotics, AI, neuromorphic computing, and ruggedized hardware signals a quiet revolution in manufacturing. Humanoids are no longer tech demos — they are becoming practical, durable assistants for factories, warehouses, and assembly lines.
The hands that can manipulate, sense, and adapt will define the next decade of industrial robotics.