Research Of Vision System In Centralized Control Soccer Robot System

Soccer robot has become one of the hot subjects in the field of robot researching, it has referred to many kinds of advanced research from different fields, actually it is a research platform which is full of high technologies as challenges. The vision system is an important part in soccer robot system as one of four subsystems, its main task is to capture images through video equipments, and obtain the position and angle information of objects through proper image process, which can provide original information for decision-making system. The speed and precision of recognition are important factors to evaluate the performance of vision system, so the emphasis in this paper is how to improve the recognizing precision and real time of vision system.The 1394 digital camera is adopted firstly to capture images as far as domestic researches. The camera can obtain superior images with high speed, which is not only easy for later image process, but also can greatly improve the real time of the system.According to the characteristics of new camera selected in this paper, RGB color model is used to process image after analyzing the several color models normally used in vision system, which can reduce the calculation in the system. A new design of color patch is introduced after analyzing the traditional color patch, which can decrease the total kinds of color used in the color patch and avoid the mutual disturbance between some kinds of colors. A set of algorithm is presented to obtain the position and angle information according to the new design of color patch. Because of the characteristics of wide-angle imaging system, geometrical distortion exists in actual images to some extent, a new kind of distortion correction model is built based on the classic model which is fit for the robot soccer competition. To recognize the objects quickly and accurately, global gridding search and modified region growing, as well as searching in a dynamic window based on the continuity of image capturing and object moving , are adopted to realize the recognition. In addition, a compensating algorithm based on circle fitting is presented in case that some part of the color patch is lost in the recognizing process. All the algorithms above are realized well through programming and debugging, it is proved that the algorithms can meet the need of real time and precision greatly for the vision system.In the last, the function of modules in the software and the program flow are presented, man-machine interface is introduced as well as its components and running result of vision system software is provided. In addition, some shortcomings are pointed out and some thoughts are given for the next development.