Automatic control is the art of making technical systems behave as we want.
Sensor fusion deals with how to combine information from different sensors in the best way, and system identification concerns data driven modelling of dynamical systems. Within robotics and autonomous systems the focus is on planning and controlling the position and orientation of a system with a minimum of manual interaction. The activities within optimization include algorithm development for model predictive control, and the complex networks area deals with different types of interactions in dynamic networks.
Examples of application areas of industrial importance are modelling and control of industrial robots, sensor fusion and decision support in cars, ships and aerial vehicles, and planning and control of autonomous vehicles.