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A Shared Multi-particle Filter for Ball Position Estimation in RoboCup Small Size League Soccer Games

机译:Robocup小型联赛足球比赛中的球位位置估计的共用多粒子滤波器

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In the RoboCup Small Size League (SSL), teams of six robots which are autonomously controlled by a team AI play soccer games using an orange colored golf ball. In SSL games, an image processing system (SSL-Vision) receives images from four cameras which are installed 4 meters above the field surface, identifies the robots and ball positions. Because the SSL-Vision identifies the robots and the ball positions from all camera images, multiple position coordinates are computed in overlapping regions of the images. A shared multi-particle filter was developed to determine the ball position in the overlapping regions, and to minimize the discontinuity of the moving ball locus across the regions. The shared multi-particle filter consists of 4 particle filters and a particle binder estimates the position of the ball from the median point of a combined distribution. In an experimental setup, the shared multi-particle filter smoothly connected two ball locus vectors with a distance of 17 mm. The distances between each sample of the shared multi-particle filter were almost the same as both sets of data from the two cameras.
机译:在Robocup小型联赛(SSL)中,六个机器人的团队由一支球队AI自主控制使用橙色的高尔夫球踢足球比赛。在SSL游戏中,图像处理系统(SSL-VISION)从四个摄像机接收图像,该摄像机安装在场表面上方4米,识别机器人和球位置。因为SSL-VISION识别来自所有相机图像的机器人和球位置,所以在图像的重叠区域中计算多个位置坐标。开发了共享多粒子滤波器以确定重叠区域中的球位置,并最大限度地减少移动球轨迹的不连续性。共用多粒子过滤器由4个粒子过滤器组成,颗粒粘合剂估计球的位置从组合分布的中值。在实验设置中,共用多粒子过滤器平稳地连接两个球轨迹矢量,距离为17mm。共享多粒子滤波器的每个样本之间的距离与来自两个摄像机的两组数据几乎相同。

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