The blue boxes are positioned. A small camera records the contents – all ready for the test. A tense Reda Jaber and Nicolas Hummel turn their heads towards the monitor. A green check appears: All in place – the boxes are filled exactly as they should be. Smiles on their faces. What seems unspectacular at first glance is technologically highly sophisticated: In Volkswagen’s Smart.Production:Lab in Wolfsburg, IT specialists Jaber and Hummel are watching artificial intelligence (AI) at work. The experiment shows: AI can independently check whether delivery boxes are packed correctly – in the laboratory or in genuine logistics scenarios.
Industrial Computer Vision is the name of the system that Reda Jaber and Nicolas Hummel have developed together with a seven-member team and in collaboration with other labs and Volkswagen’s Software Development Center in Dresden. The basic idea: people train artificial intelligence to evaluate optical data and detect errors – extremely reliably and in fractions of a second. The AI can check boxes for completeness, for example – but many other applications are conceivable. “The user interface is so simple that anyone can operate it and train the AI independently. You don’t have to be a computer scientist,” says Nicolas Hummel. Over the next few years, Volkswagen expects Computer Vision applications to generate savings in the double-digit million-euro range. The focus is on production and logistics.
Industrial Computer Vision offers a toolbox for the implementation of AI use cases: All you need is a person who prepares enough training material – for example, photos with correctly and incorrectly packed boxes – and marks them accordingly. “The AI then learns independently to distinguish faultless from faulty results. After just a few hundred training images, you can achieve good results,” says Hummel. A few days are often enough to make a neural network ready for use. Artificial intelligence – not so difficult after all with Computer Vision.