Robots of the future: Self-learning systems are revolutionizing medicine and care!

Robots of the future: Self-learning systems are revolutionizing medicine and care!

On March 28, 2025, researchers published the Learning Systems Platform a groundbreaking white paper on the integration of artificial intelligence (AI) in robotics. In particular, the potential of adaptive robots that can both learn independently and work together with people is highlighted. The co-author of the report is Prof. Dr. Elsa Kirchner, who heads the “Medical Technology Systems” working group at the University of Duisburg-Essen. In her research, Kirchner investigates how robots can be designed more efficiently to meet the requirements of a wide range of application areas.

Kirchner makes it clear that modular and universal overall systems are crucial to developing cost-effective solutions and facilitating technology transfer between different sectors. This applies both to medicine and to innovative technologies such as exoskeletons, which could potentially be used in space travel. Their work is supported by the platform, a nationwide network of experts from different areas that aims to position Germany as a pioneer in the area of ​​trustworthy AI.

The path to more flexible robot systems

The white paper addresses the urgent need to promote flexible and adaptable robotic systems that can improve their functions through interactive learning. In the future, robots will be able to learn through speech, gestures and direct interaction with people and adapt to a variety of tasks and environments. A special focus is placed on application areas such as nursing, medical technology and crafts, where intelligent systems can relieve the burden on workers.

The advances in machine learning and the associated falling costs for robots and their components are particularly interesting. This development, coupled with powerful computing architectures, enables robots to solve complex problems in real time. According to the white paper, robots learn through demonstration and human feedback, which could revolutionize their integration into nursing activities. This could give nursing staff more time for their core tasks while the robots take on simple tasks.

Technological and social challenges

Although Germany has great potential in robotics, it faces intense international competition. The Learning Systems platform emphasizes the need for interdisciplinary research to develop secure and human-centered learning algorithms. Trust in robot applications is a central issue that must be promoted through transparent and comprehensible technologies. The white paper provides development ideas, including application examples from agriculture, healthcare and recycling, and shows how adaptive robots can help optimize these sectors in the near and distant future.

The challenges and framework conditions for the development of these systems are complex, which is clearly outlined in the publication dated March 20, 2025. It is emphasized that technological, social and economic aspects must be taken into account in order to exploit the full potential of adaptive robot systems. The platform's goal remains clear: to design future-oriented, trustworthy and interactive robotics that is beneficial for both society and the economy.