Towards a Calibration-Free Robot: The ACT Algorithm for Automatic Online Color Training

Many approaches for object detection based on color coding were published in the RoboCup domain. They are tuned to the typical RoboCup scenario of constant lighting using a static subdivision of the color space. However, such algorithms will soon be of limited use, when playing under changing and finally natural lighting. This paper presents an algorithm for automatic color training, which is able to robustly adapt to different lighting situations online. Using the ACT algorithm a robot is able to play a RoboCup match while the illumination of the field varies.

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