Business Area Autonomous & Cyber-Physical Systems

With the help of autonomy we will reach the next level of automation and thus of efficiency. The elimination of manual controls will shorten the response times of systems to changes in their environment. This will make it possible to save costs and fulfill goals better. However, risks must be validated and analyzed precisely, e.g. with regard to possible endangerment of people and the environment, or the failure safety of critical systems. Challenges also exist in terms of mastering the complexity and variability of these systems. Fraunhofer IESE has been doing research in these areas for several years and is developing numerous solution components. These offers are now bundled in one business area.

Challenges

We speak of autonomy if systems can change their behavior on their own to adapt to unexpected events.

The term cyber-physical systems is used for software-based systems that control physical processes in the real world in an automated manner, such as:

  • Activation of pumps
  • Opening of weirs
  • Deactivation of wind power plants

When they are interconnected with digital services, are created. Their development and operation again entails a whole range of new challenges:

Complexity

There are various reasons for the increasing complexity of systems:

  • Total size as well as number and scope of the interfaces
  • Deployment environment (e.g., navigation of an autonomous vehicle in city traffic)
  • Task definition (e.g., coordination of delivery drones)

The solution for mastering this complexity is automation – both in terms of implementation through code generation from representations on a higher level of abstraction and in terms of quality assurance and validation.

At Fraunhofer IESE, we have a dedicated modeling method specifically for embedded systems, which was developed in the context of several national research projects and with the collaboration of leading businesses (SPES XT modeling framework). Different levels of abstraction and different views on the system simplify its use. What is important for embedded systems is that hardware aspects are treated in a special view. This approach builds on UML and SysML.

Adaptivity

Another major challenge is adaptivity: Systems must ideally adapt to changes in an autonomous manner. The usage area is often so complex that it is not fully known at development time. Solution approaches for this challenge employ adapted system architectures and system designs.

Cross-Cutting Quality Aspects

  • Functional Safety
  • Cyber-Security
  • Usability

You can find competent experts at Fraunhofer IESE for these issues. The solutions of  Fraunhofer IESE in the area of cyber-physical systems make dependencies among these quality aspects explicit, which enables early detection of defects and impact factors.

 

Success Story: Autonomous Driving