Building global map in autonomous robot soccer system
全自主机器人足球系统的全局地图构建研究

This paper is concerned with the cooperation between robots in building a global map. Based on the local map-building through multi-sensors carried by a single robot, this paper studies the monocular front-vision modeling method. Meanwhile, we elaborate two information fusion methods: density-based spatial clustering of applications with noise(DBSCAN) clustering algorithm and maximum likelihood estimate fusion algorithm. By these two methods, the information about the location of opponent robots and the information about the location of the ball are fused, thus, a global map is built. Experimental results show that through the cooperation of robots, a global map can be accurately built, which compensates the information limitation in sensors of each single robot, and meets requirements in map-building in the dynamic environment of autonomous robot soccer tournament.