From automation to autonomization
At a time when technology is evolving at a rapid pace and large amounts of data are being generated, cognitive systems are increasingly coming to the fore. They can support people in processing information and making decisions.
We offer application-specific solutions and concepts to make cognitive systems more dependable and achieve appropriate levels of autonomy.
Cognitive systems gain their cognitive capabilities through methods from the field of Artificial Intelligence. They are designed to analyze data and recognize patterns in order to draw conclusions from these. This enables cognitive systems to master complex tasks and continuously improve themselves.
Cognitive systems also include open, collaborative systems that form part of a Digital Ecosystem.
A cognitive system can be used in numerous areas with varying degrees of autonomy. In medicine, such systems support the diagnosis of complex diseases; in manufacturing, they optimize production processes; and in agriculture, they enable higher yields while reducing the use of fertilizers. Cognitive systems therefore offer enormous potential to make a decisive contribution to solving current ecological, social, and economic challenges.
Automated driving is a prime example of how difficult it can be to transfer cognitive systems into real-life application. We develop innovative safety concepts and bring a digital “safety engineer” on board.
You have an idea for a cognitive system, or you don’t know how to provide safety assurance for it?
Feel free to contact us!
For many tasks, dependability and, in particular, safety are the crucial criteria for market launch. We therefore focus on the safety assurance of Artificial Intelligence and offer solutions to control uncertainties stemming from Machine Learning processes.
In the areas of safety and security, we are paving the way for market launches and for setting new standards. This also includes methods and tools for the derivation and implementation of distributed and dynamically adaptable safety concepts.
Automated driving marks a significant milestone in the development of mobility. Through the use of Artificial Intelligence and Machine Learning, vehicles are becoming cognitive systems. Autonomous vehicles understand their environment and can react intelligently in order to ultimately reach their destination safely.
Autonomous shuttles should be integrated sensibly into a city’s existing structures and mobility concepts. Concepts such as Mobility-as-a-Service are based on cognitive systems that bring together the needs and the mobility services currently available. We identify a city’s challenges and use cognitive systems to make it more sustainable and efficient.
Thanks to their cognitive abilities, autonomous mobile robots can better assess when they can drive fast, and which evasive maneuvers are still safe. In this context, we are researching tailor-made safety concepts and corresponding safety cases in order to demonstrate the viability of the concepts.
Autonomous agricultural machines and dynamic machine fleets must perform their tasks dependably and autonomously. With tailor-made safety concepts, we help to find the right balance between costs, availability, performance, and safety.
In a confined area, robots can perform monotonous tasks not only with high precision, but also with enormous speed. However, when robots have to perform tasks in the vicinity of humans or together with humans, the speeds are surprisingly low. We are therefore researching new safety concepts that offer increased performance without taking unacceptable risks.
Collaborative robots can be used in a variety of ways, as they can be flexibly programmed for the task at hand. We are researching the possibilities of enabling robots to correctly assess the risks of an application context and to work faster.
In the healthcare sector, cognitive systems are being used to perform logistical tasks in hospitals. The applications range from medical robots to mobile autonomous robots. We support you in implementing your use case and managing any possible risks.
- We implement scientific findings and our research results in practice!
Fraunhofer Institute for Experimental Software Engineering IESE