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A fast vision system for soccer robot

机译:足球机器人的快速视觉系统

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摘要

This paper proposes a fast colour-based object recognition and localization for soccer robots. The traditional HSL colour model is modified for better colour segmentation and edge detection in a colour coded environment. The object recognition is based on only the edge pixels to speed up the computation. The edge pixels are detected by intelligently scanning a small part of whole image pixels which is distributed over the image. A fast method for line and circle centre detection is also discussed. For object localization, 26 key points are defined on the soccer field. While two or more key points can be seen from the robot camera view, the three rotation angles are adjusted to achieve a precise localization of robots and other objects. If no key point is detected, the robot position is estimated according to the history of robot movement and the feedback from the motors and sensors. The experiments on NAO and RoboErectus teen-size humanoid robots show that the proposed vision system is robust and accurate under different lighting conditions and can effectively and precisely locate robots and other objects.
机译:本文提出了一种基于颜色的足球机器人快速目标识别和定位方法。修改了传统的HSL颜色模型,以便在颜色编码环境中更好地进行颜色分割和边缘检测。对象识别仅基于边缘像素以加快计算速度。通过智能扫描分布在图像上的整个图像像素的一小部分来检测边缘像素。还讨论了直线和圆心检测的快速方法。对于对象定位,在足球场上定义了26个关键点。从机器人摄像机视图可以看到两个或多个关键点,同时调整了三个旋转角度以实现机器人和其他对象的精确定位。如果未检测到关键点,则会根据机器人运动的历史记录以及来自电机和传感器的反馈来估算机器人位置。在NAO和RoboErectus青少年型人形机器人上进行的实验表明,所提出的视觉系统在不同光照条件下具有鲁棒性和准确性,并且可以有效且精确地定位机器人和其他物体。

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