Medical robotics and training


Trend-setting topics in medical technology are robot-assisted and (partially) automated surgical interventions with networked systems and fused information. Increasing automation and increased use of AI-based assistance systems are predicted for medical interventions. Furthermore, an operating theatre is already a high-tech place, but it is equipped with many isolated devices from different manufacturers. This creates technical and regulatory hurdles that make the networked collection, documentation and utilisation of all accruing information difficult. As a result, a great potential for improved individual patient care is currently being lost.

Within the framework of LIROS, a unique research centre for robot-assisted surgery is therefore being created at Fraunhofer IMTE with a realistic operating theatre environment, modern high-end equipment and individual anatomical patient models. The focus is on the optimisation and personalisation of training, the use of imaging techniques for intraoperative navigation, the networking of medical technology devices and the investigation of usability aspects to increase user-friendliness and safety in the operating theatre.

Research into these aspects offers the potential to perform surgical interventions with unprecedented flexibility and precision and, in combination with intelligent assistance systems, to increase the quality of interventions.

Fields of research

Robot-assisted interventions and intelligent assistance systems

The use of medical robots in surgery offers the possibility of performing surgical interventions with unprecedented flexibility and precision, while at the same time relieving medical staff. Collaboration between humans and robots is of central importance here. The goal is therefore to increase the user-friendliness for humans and at the same time to provide the medical robots with a distinct understanding of their environment. To ensure this, among other things, the movements of the medical staff and the robot are tracked and, based on the collected data, gesture and voice control is implemented using data glasses. In addition, research into the interaction of collaborative robots with each other is of great interest in order to increase the degree of autonomy in the operating theatre. The use/application of various machine learning methods plays a fundamental role in each area.

Automated training evaluation and robot-assisted surgery

A system for automated recording of surgical skills based on video data has the potential for standardised and objective benchmarking. This enables individualised feedback for training purposes, which previously could only be done under expert supervision. In addition, a retrospective analysis to refine the skills is possible. At Fraunhofer IMTE, machine learning methods are used to realise an automated evaluation of training videos. In cooperation with the UKSH Lübeck, these methods will be used to evaluate and supplement a training curriculum for robotic surgery. 

Process optimisation in the operating theatre

Uniform networking of medical devices makes it possible to drastically simplify processes in the operating theatre. Instead of using proprietary networks, the goal here is a manufacturer-independent exchange of data between the devices in order to provide the user with all available information in a bundled form. On the other hand, processes in the operating theatre can also be specifically improved and accelerated. For this purpose, the network of medical devices in LIROS is expanded by various tracking systems, with the help of which not only the position of the OR team but also medical devices such as the surgical robots can be tracked and their interactions with each other analysed. With the help of augmented reality, additional information can be provided to the surgeons. Communication between the team members in the operating theatre is also of central importance, because it must function perfectly and important warning signals must be perceived in good time. In addition, voice control for operating various systems can simplify processes.


  • Workflow and system integration of medical technology devices in a modern operating theatre as well as evaluation based on test cases and usability studies.
  • Conducting studies and product testing in a realistic environment and using anatomical phantoms
  • Recording and evaluating clinical data sets using machine learning methods
  • Examination of regulatory requirements and support in the medical approval of products


  • Surgical robot systems
  • Collaborative robots
  • 3D Laparoscopy
  • Spatial Motion Capture System
  • Electromagnetic and optical tracking
  • 3D surface scanner
  • Ultrasound imaging
  • C-arm
  • AR and VR equipment