The aim of the KAMeri project is to support employees who are already working with robots today – in assembly, for example.
Based on EEG brain waves of the worker, the robot involved in the process can, for example, independently reduce speed or issue recommendations for break times, e.g. via smartwatches.
Brain Machine Interfaces are the basis for an assistance system to generate user feedback and recommendations for action and this in a real-time data transfer between platform, robot and human.
In a nutshell
The aim of the KAMeri project is to support employees who already work with robots, for example in assembly. To make this possible, a recommender system is being developed that reacts to the measured values of the worker and adjusts the machine process accordingly. For example, the robot involved in the process can independently reduce its speed or issue recommendations for break times, e.g. via smartwatches.
In order to adapt the work processes to be carried out to the individual, EEG brain waves of the workers are permanently recorded and evaluated.
In the future, machines will work closely with people in more and more areas, both spatially and functionally. Particularly in these situations, special attention must be paid to the protection and safety of people. The physically close cooperation between man and machine requires adapted and reliable occupational safety concepts.
Land der Ideen
man and machine
The August-Wilhelm Scheer Institute brings 3 crucial values to the table:
Recommendersystem. Specifically, this means the development of an assistance system for generating user feedback and recommendations for action derived from the classified information of brain waves.
Platform development. A central platform is used for data storage, analysis, control of robot systems and the necessary real-time transmission to end devices. The platform is implemented according to modern architectural patterns, using innovative technologies such as container visualization.
More detailed information about our technology stack can be found in our StackShare profile.
The KAMeri project is funded by the German Federal Ministry of Education and Research.