基于多传感器的全向足球机器人自定位

随着对足球机器人智能水平的要求进一步提高,机器人足球委员会将比赛场地的立柱、球门颜色取消.这使以前的基于球门、立柱地标的足球机器人自定位方法失效了.本文提出了一种利用了里程计、罗盘和全景摄像头多种传感器信息的视觉图像特征匹配的足球机器人自定位方法.首先,机器人通过里程计和罗盘取定一个可能位姿.然后,由视觉处理系统把机器人的可能位姿当作变换因子对实时拍摄到的场景图像作旋转、平移变换.最后,将变换后的图像中的白线与参考图像中的白线相比较,选择使图像匹配程度最大的变换因子作为机器人自定位的结果.实验结果表明该自定位方法达到了较高定位精度并能满足比赛的高实时性要求.

Self-localization of omni-directional soccer robot based on multi-sensor

Because of the increasing intelligence level of soccer robot, the international committee of robot soccer removes from the playing field the landmark information of column and goal which had been used for self-localization by many algorithms. We propose a new self-localization algorithm which utilizes the information from the compass and the odometer, and adopts the image feature-match method. First, the robot takes a possible pose via compass and odometer; and then, the vision system makes use the possible pose as a conversion factor to transform the real-time shooting image. By comparing the white lines of transformed images with the white lines of the reference image, the algorithm determines the conversion factor which makes the two images most similar as the self-localization pose. The results show that this algorithm provides high precision and meets the strong real-time requirements.