An Image Based Vision System for the Localization of Soccer Robots
In this bachelor thesis, we developed a new vision system for the Robosoccer lab at the RCS. Instead of the white markers, markers with different colors are used now to distinguish the robots from each other. Therefore we implemented a color-based classification to recognize the robots. Unlike the old vision system, where the robots and the ball are searched in the entire image, in the new algorithm we predict the positions of the objects and only search the image in small areas around these predicted positions. This contributed considerabely in reducing the processing time compared to the old vision system. As a last part of this project a kalman filter is used to reduce the effect of the camera noise on the determination of the robot's and ball's position.