In this study, we designed a localization and obstacle avoidance system for humanoid robots in the Federation of International Robot-soccer Association (FIRA) HuroCup united soccer competition event. The localization is implemented by using grid points, gait, and steps to determine the positions of each robot. To increase the localization accuracy and eliminate the accumulated distance errors resulting from step counting, the localization is augmented with image pattern matching using a system model. The system also enables the robot to determine the ball’s position on the field using a color model of the ball. Moreover, to avoid obstacles, the robots calculate the obstacle distance using data extracted from real-time images and determine a suitable direction for movement. With the integration of this accurate self-localization algorithm, ball identification scheme, and obstacle avoidance system, the robot team is capable of accomplishing the necessary tasks for a FIRA soccer game.

中文翻译：

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人形机器人足球比赛中的步态与视觉系统定位与避障

在这项研究中，我们为国际机器人足球协会（FIRA）HuroCup 联合足球比赛项目中的人形机器人设计了定位和避障系统。定位是通过使用网格点、步态和步骤来确定每个机器人的位置来实现的。为了提高定位精度并消除计步导致的累积距离误差，使用系统模型通过图像模式匹配来增强定位。该系统还使机器人能够使用球的颜色模型确定球在球场上的位置。此外，为了避开障碍物，机器人使用从实时图像中提取的数据计算障碍物距离，并确定合适的移动方向。结合这种精确的自定位算法，