Abstract
This paper presents a vision system for robotic soccer which was tested on Sony’s four legged robot Aibo. The input for the vision system are images of the camera and the sensor readings of the robot’s head joints, the output are the positions of all recognized objects in relation to the robot. The object recognition is based on the colors of the objects and uses a color look-up table. The vision system creates the color look-up table on its own during a soccer game. Thus no pre-run calibration is needed and the robot can cope with inhomogeneous or changing light on the soccer field. It is shown, how different layers of color representation can be used to refine the results of color classification. However, the self-calibrated color look-up table is not as accurate as a hand-made. Together with the introduced object recognition which is very robust relating to the quality of the color table, the self-calibrating vision works very well. This robustness is achieved using the detection of edges on scan lines.
The Deutsche Forschungsgemeinschaft supports this work through the priority program “Cooperating teams of mobile robots in dynamic environments”.
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© 2005 Springer-Verlag Berlin Heidelberg
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Jüngel, M. (2005). Using Layered Color Precision for a Self-Calibrating Vision System. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds) RoboCup 2004: Robot Soccer World Cup VIII. RoboCup 2004. Lecture Notes in Computer Science(), vol 3276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32256-6_17
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DOI: https://doi.org/10.1007/978-3-540-32256-6_17
Publisher Name: Springer, Berlin, Heidelberg
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