A quartet of industry heavyweights has joined forces to tackle one of the most stubbornly manual hurdles in automotive manufacturing. Audi AG, robotics unicorn Agile Robots, simulation giant Dassault Systèmes, and AI powerhouse NVIDIA have announced a proof-of-concept to deploy mobile humanoid robots at Audi’s Ingolstadt plant in Germany. The mission? To automate the grueling parts-sequencing process—a logistical ballet that requires around one million individual picks every single day.
The project, unveiled at NVIDIA GTC Berlin, aims to crack a problem that has plagued automation experts for decades: how to reliably pick a vast variety of unsorted, often flexible parts out of containers. At Audi’s “Production Lab”, mobile humanoids from Agile Robots will be tasked with grabbing components and placing them in the precise sequence required for final assembly. Before a single physical robot even sets wheels on the factory floor, the entire workflow is being meticulously choreographed in a virtual twin of the plant. This digital rehearsal is built on Dassault Systèmes’ 3DEXPERIENCE platform and its DELMIA application, leveraging NVIDIA Omniverse libraries to ensure the simulation is physically flawless.
The star of the show is the mobile humanoid from Munich-based Agile Robots. Combining a mobile base with dual arms, the robot operates at human height, allowing it to slot into existing infrastructure without requiring a costly factory overhaul. Its AI-powered perception and dual-arm manipulation are designed specifically to handle the complex and variable parts that have traditionally defeated rigid automation—essentially solving the industrial equivalent of finding a specific Lego brick in a giant, unsorted bin.
Why does this matter?
This collaboration is more than just a flashy pilot; it’s a significant bellwether for the future of industrial automation. Firstly, it validates the “simulation-first” philosophy. By using a sophisticated virtual twin, Audi can de-risk the project and slash deployment time from months to mere days, proving the business case for the industrial metaverse. Secondly, it offers major commercial validation for mobile humanoids in a real-world, high-stakes environment, moving beyond scripted demos. For decades, sequencing has been too complex for traditional robots, but this project suggests that “Physical AI” is finally ready to graduate from the lab.
For Audi, this is a concrete step towards its “thinking factory” vision, offloading repetitive, ergonomically punishing tasks from human workers to their robotic counterparts. If successful, this proof-of-concept could provide the blueprint for automating one of the most critical and labour-intensive processes in automotive logistics, fundamentally shifting the gears of modern car manufacturing.
