Unseq wants to remove humans from one of aviation’s toughest jobs

“After five years, their shoulders break down. Their backs break down. It’s a job that should not be done by humans.”

Most airline passengers barely think about what happens to their suitcase after check-in. Somewhere between the terminal and the aircraft, every bag still depends on human muscle power. In the cramped belly of an airplane, baggage handlers crouch, twist, lift, and shove hundreds of heavy suitcases into place before every flight.

For Robert de Bruijne, that invisible physical labor has become the starting point for a deep-tech robotics company with ambitious plans for aviation automation. During the April edition of Gerard & Anton’s Demos, Pitches & Drinks in Eindhoven, De Bruijne introduced the audience to autonomous baggage grasping and manipulation

The problem, he explained, is both enormous and largely overlooked. “If you fly to a destination in Europe, there are obviously a lot of bags in the airplane, probably also your bag,” De Bruijne told the audience. “Right now, there are two people moving those bags around.”

He showed footage of the loading process: baggage arriving via a belt loader and then being manually stacked deep inside the aircraft hold by workers operating in an extremely confined environment. What passengers rarely see, according to De Bruijne, is the physical toll this work takes. “The two people there in the hold basically last five years,” he said. “After five years, their shoulders break down. Their backs break down. It’s just a job that should not be done by humans.”

That challenge forms the core mission of Unseq: replacing one of aviation’s most physically demanding jobs with autonomous robotics powered by advanced AI systems.

A robot for the aircraft belly

Unlike warehouse automation, baggage handling inside aircraft presents a uniquely difficult robotics problem. Cargo holds are cramped, irregularly shaped, and filled with luggage of wildly different sizes, textures, and weights. Every suitcase behaves differently. Every aircraft type has its own geometry.

To tackle that complexity, Unseq is building a fully custom robotic system, including its own AI networks for autonomous baggage grasping and manipulation. “This is a fully custom system running on our own AI networks,” De Bruijne explained.

The company has already built a realistic testing environment. In their lab, the team reconstructed the interior shape of aircraft holds using wooden panels. The luggage itself came from thrift stores. “All the baggage you see is collected from thrift stores,” De Bruijne joked.

What he could not show publicly was perhaps the most important part: the full-scale prototype itself. “Where I’m standing now in this picture is our real full-scale prototype,” he said. “I cannot show pictures due to intellectual property constraints.”

That secrecy reflects how strategically important automation is becoming within aviation logistics. Airports worldwide face labor shortages, increasing passenger volumes, and growing pressure to improve working conditions while maintaining operational speed.

Physical AI moves into the real world

Unseq’s approach sits within a broader new wave of robotics, often referred to as “physical AI”, systems that combine machine learning with real-world manipulation of objects.

On stage, De Bruijne referred to technologies such as reinforcement learning and advanced neural network architectures that enable robots to autonomously grasp and move unpredictable objects.

To accelerate development, the company also built a smaller tabletop-scale experimentation platform. “It enables really fast experimentation,” he explained. “You can try new networks, new things, without breaking very expensive hardware.”

That combination of simulation, scaled experimentation, and full-size testing mirrors techniques increasingly used by leading robotics companies worldwide. Instead of programming every movement manually, modern AI-driven robots learn behavior through large numbers of iterations and training cycles.

The challenge is especially difficult in baggage handling because soft suitcases, backpacks, rigid trolleys, and oddly shaped luggage all behave differently when grabbed, lifted, or stacked. For robotics researchers, it is a classic manipulation problem. For airports, it could become a major operational breakthrough.

Eindhoven robotics ecosystem

De Bruijne used the pitch not only to present the company, but also to recruit talent and investors from the Eindhoven ecosystem. “We’re really looking for people in the robotics domain who use the same technology as we do,” he said. “There aren’t so many people in it.”

Specifically, Unseq is searching for specialists in reinforcement learning, robotic grasping, and AI-driven manipulation systems. The company is also raising a pre-seed investment round aimed at helping the startup reach its next technical milestones. “We are looking for investors that understand robotics and the deep-tech domain,” De Bruijne said.

The pitch illustrated how Eindhoven’s startup scene increasingly extends into fields where AI, robotics, and industrial systems converge. It also highlighted a recurring theme within the region’s innovation ecosystem: using advanced technology to solve very physical, real-world labor problems.

In Unseq’s case, the goal is remarkably tangible. Every suitcase loaded into an airplane today still depends on human bodies operating in uncomfortable and physically damaging conditions. If the Eindhoven startup succeeds, future passengers may never notice the difference. Their bags will still arrive. But inside the aircraft hold, the humans may gradually disappear.