Abstract
In this paper, a fast and robust algorithm is presented for color-blob tracking, which is applicable in a multi-robot cooperative control system. The algorithm, which is immune to uneven illumination, identifies the current poses (positions and orientations) of a robot and the manipulated object (a rectangle box) from a color image, in real time. Two main challenges are faced in the multi-robot task considered in the paper. The first one concerns the response speed of the vision subsystem. The second challenge comes from uneven lighting, which makes it very difficult for the vision subsystem to trace a specific color blob in different positions. A fast computer vision algorithm is presented to cope with these challenges. First, an image in the RGB (Red-Green-Blue) color space is converted into the HSI (Hue-Saturation-Intensity) color space. Then the Saturation and the Intensity components of the image are removed and only the Hue component is retained. Second, filtering and template matching technologies are employed to remove the disturbances from the background and other objects in the image. Finally, coordinate transformations are used to reconstruct the poses of the robot and the object when they are moving. A multi-robot route planning approach is presented, which uses the information acquired by the color-blob tracking algorithm. The experimental results are presented to show the feasibility and the effectiveness of the algorithm.
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