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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用于球位置估计的共享多粒子滤波器

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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,由六个AI团队自主控制的机器人组成的团队使用橙色高尔夫球来踢足球。在SSL游戏中,图像处理系统(SSL-Vision)从安装在战场表面上方4米处的四个摄像机接收图像,识别机器人和球的位置。由于SSL-Vision可从所有摄像机图像中识别机器人和球的位置,因此会在图像的重叠区域中计算多个位置坐标。开发了共享的多粒子过滤器,以确定重叠区域中的球位置,并最大程度地减小了跨区域移动球轨迹的不连续性。共享的多粒子过滤器由4个粒子过滤器组成,粒子粘合剂从组合分布的中点估计球的位置。在实验设置中,共享的多粒子滤波器平滑地连接了两个球轨迹矢量,距离为17 mm。共享多粒子滤镜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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