London Gatwick becomes first UK airport to deploy robotic parking, no keys required

Gatwick becomes first UK airport to deploy robotic parking with Stanley Robotics

London Gatwick has become the first UK airport to introduce robotic parking. Passengers drive into a private cabin near the South Terminal, leave their car, and keep their keys. An autonomous robot built by Stanley Robotics slides underneath the vehicle, lifts it by its tyres, and transports it to a secure storage area. First paying customers start in August 1.

Stanley Robotics is a deep tech company headquartered in Paris that builds autonomous robots for outdoor logistics. Founded in 2015, the company describes itself as the creator of the world's first outdoor robotic valet parking service. The Gatwick deployment is its first at a UK airport, though it has installed similar systems at airports internationally 12.

How Gatwick's robotic parking works

Passengers book in advance, drive into an enclosed cabin, and scan their booking. They park, step out, and keep their keys. A Stanley Robotics robot then lifts the car by its tyres and moves it to a secure storage zone. Because no one needs to access the vehicle once it is stored, cars can be positioned closer together than in a conventional car park, increasing capacity without new construction 1.

On the return trip, passengers have already provided their flight details during booking. The system monitors their arrival and has the car waiting in a collection cabin. The facility is within walking distance of the South Terminal, with a free shuttle bus as an alternative. On-site staff can retrieve essential items if a passenger accidentally leaves something inside the vehicle 1.

The service covers most standard passenger cars: maximum weight 2.6 tonnes, maximum height 2.3 metres, maximum wheelbase 3.3 metres, maximum wheel diameter 21 inches. It must be booked ahead. No same-day drive-up parking 1.

Why parking, not robotaxis

Gatwick's robotic valet is one of the earliest autonomous-robotics deployments that ordinary consumers will physically interact with. Not a self-driving taxi on public roads. Not a humanoid robot in a factory. A machine that picks up your car, stores it, and returns it before your flight lands.

The reason parking arrives before higher-profile autonomy is structural. Airport parking lots are fenced, predictable environments with a single operator. If the robot encounters a problem, a human intervenes and the worst outcome is a delayed car. The task itself (lift, move, store, retrieve) is narrow and repetitive, the kind of job where reliability compounds with every cycle.

Contrast that with robotaxis operating on public roads among unpredictable drivers, navigating a different regulatory framework in every city, or humanoid robots attempting open-ended tasks in unstructured environments. Both are harder problems with higher stakes for failure. The infrastructure layer (parking, warehouse logistics, last-mile delivery) is where physical AI builds the operational track record that makes harder deployments possible.

The capacity business case

Gatwick has a concrete reason to adopt this beyond novelty. Stanley Robotics was founded in 2015 to bring warehouse-style storage density to outdoor logistics 2. For an airport constrained by land and planning permissions, tighter car packing translates directly into more vehicles per square metre without building new parking structures.

Oli Bedford, Head of Airport Access, Marketing and Commercial Products at London Gatwick, framed the service around speed and convenience for passengers 1. Clement Boussard, CEO of Stanley Robotics, said the Gatwick project would help the airport address parking demand as it prepares for growth 1.

What this proves

Each airport deployment adds a controlled, repeatable proof point: autonomous robotics can handle a consumer-facing task with paying customers and a service-level expectation. The technology here is not dramatic. A robot lifts a car by its tyres and carries it to a storage slot. But the unglamorous deployments are the ones generating the reliability data that determines whether physical AI moves from warehouse demos to daily life.