Control Systems commonly use "simple" sensors that directly quantify the required measure (e.g., angle, temperature, voltage, ...).
Today, however, more and more Control Systems rely on vision-based sensors (i.e., cameras) to allow for more complex and less intrusive control scenarios. In contrast to "simple" sensors, vision-based systems require additional processing power to extract the required measure from the camera images. As the Image Processing Algorithms are part of the control loop, their processing time (delay) and variation therein (jitter) has to be considered and monitored carefully. Furthermore, as the Vision-based sensing won't be 100% accurate, the resulting error has to be incorporated into the design flow.
To investigate these challenges, a test setup based on a Levitating Ball is being developed.

The goal of this thesis is to port an existing, non-real-time tracking application to a real-time operation system.
The existing Tracking Application is written in C++ and - currently - is executed as regular task in Linux. Using both commercial and open-source libraries, it acquires a continuous video stream from an Ethernet camera, performs image processing plus control calculations and transmits the control output via UDP. It accomplishes a reasonable, yet not completely smooth, levitation of the plant under consideration, a Levitating Ball.
To improve the performance (i.e., achieve a more stable levitation), this Application shall now be executed using a Real-Time Operating System (RTOS) running on a regular Standard PC (AMD64 platform).