Safety engineering

The new Fraunhofer IKS Safety Companion is an AI agent designed to support human developers with safety-critical tasks. It uses large language models (LLMs) to understand tasks and to identify and implement the appropriate safety concepts. Executive Director Mario Trapp and Florian Geissler, Senior Scientist at Fraunhofer IKS, introduce the Safety Companion in an interview.

As production technologies continue to evolve, it can feel like companies are permanently playing catch-up. Read on to understand the current key changes in industrial automation and why it is worthwhile to embrace them.

Robots can relieve people of many tasks – but only as long as they work. And as soon as a fault occurs, the time-consuming search for its cause begins. In contrast to conventional software development, robots have even more areas in which bugs i.e., errors could be hidden. Especially once the development has progressed and the interaction between the robot and its environment is considered. A field report from the world of research.

There are still several technical and regulatory obstacles to overcome before autonomous cars are ready for mass production. But when it comes to rail transport, things are much further ahead. Self-driving trains are already a common mode of transport. But how exactly does autonomous driving on rails work?

Holistic safety for road vehicles is the focus of Safetronic conference (15-16 November 2023 in Leinfelden-Echterdingen). In the video interview, Fraunhofer IKS Institute Director Prof. Dr. Mario Trapp and program committee member Hans-Leo Ross from Vay Technologies discuss safety challenges in the automotive sector.

With his work, Prof. Dr. Simon Burton is seeking to make AI safer. The key question that drives him: How can we reduce the technical risk associated with complex autonomous systems in a demonstrable way?

The safetronic® is the industry's premier conference for the holistic safety of road vehicles. In November 2022, experts from the automotive industry met again to discuss challenges, solutions and trends. Although the safety of automated vehicles and, in particular, the associated safety assurance of AI are currently in the public spotlight, the experts at the conference had a different perspective. For them, a well-known topic is experiencing a revival and is emerging as a new trend topic: model-based system safety engineering (MBSE). Having worked on model-based safety engineering for well over a decade now, I'm personally as intrigued by this trend as I am skeptical about whether it's going to take off this time. That's reason enough for me to take a closer look at this potential trend from my individual perspective in this article.

Two leading experts from the Fraunhofer IKS and the University of York in the safety of complex systems have published a paper proposing a new approach to assure the safety of cognitive cyber-physical systems (CPS), including automated driving systems.

The standardized architecture of the Fraunhofer IKS integrates any automated driving function into an existing automated verhicle.

Safety is a property of a system and its environment. That's why predicting a system's context is so important to safety engineers. However, we must acknowledge that it is impossible to sufficiently predict and specify a system's context when it must operate outside of a controlled environment. In the previous parts of this series, we've seen how we can use self-adaptivity to build systems for uncertain, dynamic contexts. In this fourth and final part, we add the missing ingredient by taking safety engineering to the next level.

What are the basic principles of self-adaptive systems? This is the basic prerequisite for bringing the concept of resilience to life. Part 3 of our series.

Resilience is the key ingredient for the next generation of cognitive cyber-physical systems. After all, many visions of the future can only become reality if the systems become aware of themselves, their goals and their context in order to be able to adapt to unknown and changing environments. And in doing so always optimize utility while preserving safety. But resilience can only be bought with increased complexity. In this article, part 2 of our series on resilience, we look at the character of complexity to better understand where to start engineering in order to manage this complexity.

Resilience is a key ingredient for lifting cars, industrial manufacturing and medical devices to the next level. It is far more than a fancier synonym of dependability. And the aspect that resilience is standing for is essential for building cognitive systems. That's why resilience is the focus of a new series on the Safe Intelligence Blog. In the first part, we will look behind the term and clarify why resilience is so important and why it is more than just a synonym for dependability.

The international conference Safetronic holistically addresses the safety of road vehicles. Abstracts for conference papers may be submitted until May 9, 2022.

The EAI IC4S international conference has awarded the prize for the best paper to Fraunhofer IKS. The topic of the paper is a concept for safe and efficient collaboration between autonomous mobile robots (AMR) and people in shared areas.

The system in autonomous vehicles must be able to reliably detect pedestrians. Deep learning approaches are the main method used for this task. However, in comparison with classic software, the results of these approaches must also be checked and verified, which requires various complicated technical measures. This article provides an overview of these measures.

In the field of modern warehouse logistics, speed is crucial to success. This is where autonomous mobile robots (AMR) come in. In order to perform their tasks, they must respond as flexibly as possible to new environmental conditions and warehouse goods. ResilientSOA, the framework developed by Fraunhofer IKS, provides the necessary prerequisites. In this interview, project manager Florian Wörter explains exactly how it works.

For autonomous vehicles to move smoothly and safely through road traffic in the future, they must be able to communicate with other road users and with the traffic infrastructure. To support the communication, Fraunhofer IKS has developed a new approach for such hybrid perception.

Having finished her studies in computer science, Marta Grobelna is working at the Fraunhofer Institute for Cognitive Systems IKS and planning her doctorate. She particularly appreciates the practical relevance of her research work in the area of safety engineering. Part 11 of our employee profile series.

A simulation designed by Fraunhofer IKS paves the way for robots and humans to interact safely — without reducing efficiency.

Fraunhofer IKS is carrying out research into safe software applications for quantum computers. The work is part of the new Bavarian initiative Munich Quantum Valley.

Science needs to prove that systems based on artificial intelligence (AI) are safe enough. That is what Prof. Simon Burton, who recently became Division Director for Safety at Fraunhofer IKS, is calling for. In this interview he explains the institute’s approaches to ensuring safety.

Flexible service-oriented architectures (SOAs) in safety-critical applications have been virtually out of the question until now. This is because services need to be reliably available and safety requirements need to be met at all times. Fraunhofer IKS has developed resilientsoa, a software framework that meets these needs by ensuring that service orchestration is as safe as necessary while performing as well as possible.

Machine learning means a disruptive challenge for safety assurance. Without an acceptable safety assurance concept, many great ideas will not find their way to the market. It’s therefore no surprise that AI safety has gained much more attention over the past few months. A brief series of articles will take a closer look at the importance of safety for AI. The first article focuses on the basic understanding of what safety actually means. It highlights why it is so important to understand that safe AI has less to do with AI itself and much more to do with safety engineering.