Mercedes-Benz has significantly deepened its integration of robotics within its global manufacturing network and has now taken a pioneering step with the introduction of humanoid robots on the factory floor. This development was highlighted by Dr. Jörg Burzer, Chief Operating Officer of Mercedes-Benz Group AG, during his keynote address at the European Robotics Forum 2025, held in Stuttgart.
Expanding an Already Extensive Robotics Fleet
With more than 30,000 robots operating across over 30 global production sites, Mercedes-Benz has long been a frontrunner in applying automation to automotive manufacturing. These robots are deployed across body shops, assembly lines, and even paint shops, carrying out over 50 types of processes. Burzer noted that some robots in their network handle loads of up to 1,000 kilograms with tolerances as precise as 500 micrometers.
Mercedes-Benz’s production operations, supported by around 80,000 employees from over 100 nationalities, produce approximately 2.4 million vehicles per year. The integration of robotics, Burzer emphasized, is essential to maintaining sustainable, efficient, and high-quality manufacturing practices, particularly as the industry transitions toward electrification.
Introduction of Humanoid Robot “Apollo”
In a notable update, Mercedes-Benz has begun using humanoid robots, branded as “Apollo,” developed by U.S.-based startup Apptronik. These robots were first introduced at a plant in Hungary and are now being rolled out in Berlin, home to the company’s Digital Factory Campus.
Apollo is designed to perform physically demanding and repetitive tasks, such as lifting, assembling, and handling heavy components. Initial applications focus on two areas: quality inspection—particularly exterior and interior visual checks—and internal logistics, where the robots assist with moving loads in potentially hazardous conditions. Burzer emphasized that these robots are intended to augment human workers, not replace them, by taking over strenuous tasks and thereby enabling teams to concentrate on higher-value activities.
A Data-Driven Ecosystem
Robotics at Mercedes-Benz operate within a broader digital infrastructure. The company’s MO360 digital production ecosystem, developed in collaboration with Microsoft (Azure) and Siemens, collects and analyzes approximately two terabytes of data daily. This data is used to manage and optimize operations, including robotics performance, energy efficiency, and quality control.
MO360 is accessible to over 50,000 users across the company’s global production facilities, with tools supporting digital shop floor management, AI-based quality management, and predictive maintenance. The system also features integration with Nvidia’s Omniverse platform, enabling virtual factory planning and the simulation of robot placement within digital twins of production environments.
Artificial Intelligence as a Core Enabler
AI has become an integral part of Mercedes-Benz’s production strategy. The company uses AI-powered chatbots to support workers on the line, providing immediate access to standard procedures and real-time data insights. In painting operations, AI algorithms have already helped reduce energy consumption by 20%.
According to Burzer, Mercedes-Benz’s approach involves combining mechanical robotics with AI and cloud infrastructure to drive process innovation. The company is also working on democratizing data access across its workforce, allowing teams to create and apply AI models directly in production settings.
Looking Ahead: Humanoids and Automation’s Evolution
Burzer acknowledged that the physical form and specific use cases of humanoid robots in production will evolve. For now, Mercedes-Benz is focusing on the most complex scenarios with Apollo, which could later be scaled or adapted to simpler forms. Applications like part picking and transport in logistics, as well as enhanced quality assurance, are likely to expand as the technology matures.
He concluded by inviting the robotics community to collaborate, stressing that innovation in manufacturing increasingly depends on the integration of data science, robotics, and artificial intelligence.
