A Real-Time Auto-Adjusting Vision System for Robotic Soccer

This paper presents a real-time approach for object recognition in robotic soccer. The vision system does not need any calibration and adapts to changing lighting conditions during run time. The adaptation is based on statistics which are computed when recognizing objects and leads to a segmentation of the color space to different color classes. Based on attention, scan lines are distributed over the image ensuring that all objects of interest intersect with the number of lines necessary for recognition. The object recognition checks the scan lines for characteristic edges and for typical groupings of color classes to find and classify points on the outlines of objects. These points are used to calculate size and position of the objects in the image. Experiments on Sony’s four-legged robot Aibo show that the method is able to recognize and distinguish objects under a wide range of different lighting conditions.