DigiT4TAF-BW
AI in the Mobility Sector
Artificial Intelligence (AI) as a key technology enables and enhances many research projects at the FZI – especially in the application fields of Mobility, Transportation and Logistics, but also in Production, Supply and Disposal, as well as Healthcare.
AI plays a strong role in the FZI’s research on human-robot collaboration, functional safety – especially for robotics and mobility – or sensor and image processing solutions across all subjects.
A particular concern of the FZI is to evaluate the latest AI methods and procedures from research, adapting and transferring them into practical applications at partner companies.
The FZI is particularly adept in the area of Applied Artificial Intelligence concerning criteria of transparency, coherence, and security.
Within the Applied Artificial Intelligence research focus, the FZI will spotlight the continuous expansion of the topics of human-in-the-loop processes, embedded neuromorphic computing and self-supervised learning. Enhancing the expertise in the area of evaluating and generating texts in natural language – namely Natural Language Processing (NLP) – is an especially high priority. Topics such as Reinforcement Learning and knowledge representation are included increasingly.
The goal is to develop representations of knowledge, such as language, which can be used by humans as well as for AI methods. This is necessary, for example, in the automotive sector, in media and communications (i.e. for the analysis and recognition of disinformation campaigns), or for Industry 4.0. Furthermore, end-to-end learning methods help improve the compliant control of robot arms. Moreover, the reactivity of robot systems can be increased efficiently through the skilful use of pre-learned movements.
What distinguishes the FZI’s work with Artificial Intelligence is its closeness to the application and its strength in engineering AI systems. Approaches are always based on systematic thinking, from the AI function to the realisation. For the FZI, applying AI in embedded systems with restrictions in terms of resources, energy, or interfaces is a focus. It is essential to include the constraints of the hardware boundary conditions in a consistent design during the early development stages. The FZI benefits from its well-equipped laboratory environment with real application scenarios for practical relevance.
Digital Hub Karlsruhe, AI Regio, FZI AI Day
AI in the Mobility Sector
Supercomputing Platform for Highly Automated Vehicles
Data management repository for care-supporting AI applications
Automatic Integration of Avionik Racks via Artificial Intelligence
Flexible refrigeration systems against the background of increased decarbonization
European Digital Innovation Hub applied Artificial Intelligence and Cybersecurity
Living lab for the transfer of digital health applications and AI into healthcare
Next-generation distributed, continuously learning onboard power management system
Broker for dynamic production networks
Leadership development for firefighters via intelligent virtual realities