Projects and products of the department MRD

Whether you’re a pioneer from industry, an SME, a skilled-trades business, the municipal or government sector, or an emergency services organization: As the Fraunhofer IOSB’s Humanoid Robots Experience Lab (HREL), we offer you low-threshold, hands-on access to humanoid robotics.

Das Fraunhofer IOSB hat eine KI entwickelt, die auf Basis aktueller Messwerte den Alterungszustand eines Katalysators zur Methanoxidation (Reinigung der Abgase von Schiffsmotoren) bestimmt.

The tools and concepts developed are intended to enable property managers and external service providers to optimize control loops (e.g., flow temperature setpoints) with minimal effort and in line with specific needs, and to immediately monitor the effectiveness of the measures.

The Karlsruher Forschungsfabrik for AI-integrated production offers the special opportunity to research and develop the topic of “Intelligent Production” in a practical way on real processes.

The ResilVerbund project focuses on the AI-supported monitoring and forecasting of biodiversity and water quality in drinking water reservoirs.

Concepts and procedures for the robust localization and navigation of underwater vehicles and for the realization of the planned inspection and exploration capabilities are developed.

The Potential pilot AI is a compact, modular solution that offers medium-sized companies a cost-effective way to evaluate the potential of AI processes in their production processes.

In this cooperation project, an intelligent system is to be designed and implemented as a prototype that enables the rapid detection and precise localization of leaks in district heating networks based on data and, based on this, calculates response strategies for shutting off network sections while ensuring an optimal supply to end customers.

Understanding real traffic - safeguarding automated mobility. The safe introduction of highly and fully automated vehicles depends crucially on how well we can digitally map today's traffic events - especially critical situations. AVEAS develops scalable, data protection-compliant methods for systematically recording and modeling risk-relevant scenarios and transferring them to virtual test environments.

Das Projekt CC-King hat sich zum Ziel gesetzt, KI-Spitzenforschung mit etablierten Ingenieurdisziplinen zu verbinden. Hierdurch sollen KI-Methoden und maschinelle Lernverfahren (ML) entsprechend den typischen Anforderungen und Vorgehensweisen von Ingenieuren nutzbar gemacht werden.

In order to keep the total operating costs of wind turbines (WTGs) competitive, the risk of failure must be minimized, maintenance costs reduced, and system availability and energy efficiency increased. This goal is achieved by introducing the most efficient, automated multi-sensory online monitoring and diagnostic systems - so-called Condition Monitoring Systems (CMS) - whose economic importance is increasingly recognized by wind farm operators, manufacturers and insurers.

The W-Net 4.0 project aims to develop a modular and scalable platform that combines GIS system, simulation software and data analysis tools and meets high IT security standards. Combined with novel service concepts, value-added networks and training concepts, small and medium-sized water supply companies will be enabled to use these technologies for the first time. For large utilities, novel and easy-to-use data analysis and optimization tools as well as corresponding service concepts will be made available.

The RICE project was launched as part of the technology development program to develop tools that can collect plant data in a minimally invasive manner and actively intervene in processes. The long-term goal is to improve the efficiency of industrial manufacturing systems.

AI-supported recording and forecasting of biodiversity and water quality in drinking water reservoirs.

Multisensory system for AI-based drone detection and classification with situation visualization.

“AutoInspect” is a system for continuous object assessment (in real time) by multimodal inspection along the production cycle. Both a direct reaction to the results and their long-term observation are possible. The system is supported by a digital quality twin with open I4.0 standards.

The deflectometric measurement method uses specular reflection: mirror images of known patterns in the surface and their deformations are observed to automate the quality inspection of painted car body parts, for example.

The idea of Team ARGGONAUTS, with which Fraunhofer IOSB competed in the Shell Ocean Discovery XPRIZE technology competition and finished among the top 5: autonomous catamarans tow lightweight diving drones into the field, where they single-handedly map the seabed at depths of up to 4000 metres.

The Competence center “Robot systems for decontamination in hazardous environments” is the research center for autonomous or semi-autonomous robot systems, which are to be used in practical applications where work has so far been associated with a considerable risk potential for humans.

Digital technologies and platform for the forecasting and operational optimization of drinking water supply systems.