The Digitalization Technologies-Team at ZAL GmbH in Hamburg brings artificial intelligence to aviation and offers cutting-edge technologies to the industry. Here you can get an insight into the innovative work of our experts in the field of artificial intelligence using the example of three current research topics.



Artificial intelligence already helps us today in our everyday lives: It parks our car, it compiles news feeds, it recognizes our face, our voice and identifies diseases in our x-rays. Artificial intelligence is also finding its way into the industry, making production processes safer and more efficient. As the employed algorithms often behave like a black box, this technology can only be used to a limited extent for safety-critical systems. A limiting factor in the aviation industry with its very high safety standards. For this reason, our experts work on how artificial intelligence can be made transparent, trustworthy and comprehensible in order to enable its use in aviation. The field of research dealing with this form of artificial intelligence is called X-AI (explainable artificial intelligence).


Robotics and AI
Another research focus is the combination of robotics and AI. Robots can handle tasks that are too exhausting, too repetitive or too unsafe for humans. They are also used when the highest demands are placed on precision and reproducibility. In order to develop robots from rule-based automats towards smart helpers, robots must also be able to navigate in a dynamically changing environment and, for example, distinguish humans from static obstacles. In this context, the experts of ZAL R&T use technologies such as image recognition to enable robots to see and understand their environment. Within its technological capabilities, this subtype of artificial intelligence can be used universally and make processes in production and manufacturing, but also in structural health monitoring or logistics, more efficient and safer.


Synthetic Data
Data is the new oil - it powers the engine room of deep learning (a subcategory of artificial intelligence) and facilitates the interpretation of complex data streams such as human language. Unlike oil, data is not finite in general but is often insufficient or of insufficient quality for a particular problem. That is why the team of experts focuses on synthetic, artificially generated data. A robot that was trained in a virtual environment can then operate in the real world. The challenge that this approach works despite the unavoidable differences between synthetic and real data is something our Digitalization Technologies-Team addresses.




Dr. Leonid Lichtenstein
Center of Competence Digitalization Technologies
Tel.: 040 248 595 143, E-Mail: leonid.lichtenstein(at)