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    Home » BMW tests AEON humanoid robots in German production
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    BMW tests AEON humanoid robots in German production

    March 11, 2026
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    EuroWire, LEIPZIG: BMW Group has launched a pilot project using humanoid robots in production at its Plant Leipzig, marking the company’s first deployment of humanoid robotics on a factory floor in Germany. BMW announced the project on Feb. 27 and provided additional details on March 9, describing the move as part of what it calls “Physical AI,” which combines artificial intelligence software with machines operating in real production processes. The company said the pilot is being carried out with Hexagon Robotics, an organizational unit of Hexagon focused on robotics and related software.

    BMW Plant Leipzig begins pilot testing humanoid robots in production and logistics. (Credit – BMW Group)

    BMW said the humanoid robot, named AEON, is designed to move through production areas on wheels and to use interchangeable hands, grippers and scanning tools depending on the task. At Leipzig, BMW said the robot will be tested for work steps linked to high-voltage battery assembly and component manufacturing. The company said AEON is also being evaluated for internal logistics support, including delivering materials to the line and navigating around obstacles while operating inside an active factory environment.

    BMW said the Leipzig effort follows a staged evaluation process that starts with theoretical assessment and laboratory trials and then moves into real production conditions. After laboratory tests, BMW said a first test deployment at Plant Leipzig was completed in December 2025. A further test deployment is planned from April 2026, with step-by-step integration into BMW’s production system ahead of a pilot phase scheduled to start in summer 2026. BMW said a new Center of Competence for Physical AI in Production will coordinate evaluation and integration across its production network.

    Production data and integration

    BMW said development of humanoid robotics in its factories is tied to a unified IT and data model across its production network. The company said it has consolidated production data into a standardized platform intended to keep information consistent and available across sites. BMW said artificial intelligence is already used in multiple steps, including virtual factory planning with digital twins, AI-supported quality checks and intralogistics supported by autonomous  transport  solutions. BMW said this foundation supports learning systems and robots operating in complex production environments.

    BMW said humanoid robots are being added as a complement to existing automation, with early use cases focused on monotonous, ergonomically demanding or safety-critical tasks. The company said Hexagon Robotics, based in Zurich, presented AEON in June 2025, and that BMW has worked with Hexagon for years in sensor technology and software. BMW said Plant Leipzig is the initial European site for testing how a humanoid system can be integrated into established series production processes alongside existing robotics and material flow systems.

    Earlier BMW trial in the United States

    BMW said its first plant deployment of humanoid robots took place in 2025 at BMW Group Plant Spartanburg in the United States, in collaboration with technology company Figure AI. The automaker said the robot Figure 02 supported production of more than 30,000 BMW X3 vehicles within ten months, working 10-hour shifts from Monday to Friday. BMW said the pilot showed humanoid robots can carry out precise, repetitive steps, including positioning components with millimetre accuracy, and said the test required early coordination across production IT, occupational safety, process management and shop floor logistics.

    BMW said AEON stands about 1.65 meters tall and weighs about 60 kilograms, and it can move through the plant at speeds up to 2.5 meters per second. The company said the robot is intended to support workers rather than replace them, and that the Leipzig pilot is focused on identifying repeatable tasks that can be performed safely in a production setting as testing proceeds through the planned deployment phases.

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