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Ball detection algorithm for robot soccer based on contour and gradient hough circle transform

机译:基于轮廓和梯度Hough圈变换的机器人足球球检测算法

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Kontes Robot Indonesia (KRI) changes their rule every year. This paper proposes a new ball detection method in response to the changes of the rules on Kontes Robot Sepak Bola Indonesia (KRSBI) division for KRI 2017. For the humanoid division the ball is changed from the orange tennis ball in previous year's competition to a white, size 1 FIFA soccer ball. For the wheeled division an orange size 4 FIFA soccer ball will be used. The algorithm proposed in this paper is based on the contour and Gradient Hough Circle Transform (GCHT) which is capable of detecting balls of any color. The contour based will be primarily used to detect the ball and the GCHT will be used for the second chance if the robot fails. Experiments show that the proposed algorithm can achieve ball detection accuracy of 100% (orange ball) and up to 96% (white ball) fixed-placement experiment. In random-placement experiment, the proposed algorithm achieved an accuracy of 93.3% (orange ball) and 96.6% (white ball). Furthermore, the processing time observed in the experiments is quite fast, averaging at 37.76 FPS.
机译:Kontes机器人印度尼西亚(KRI)每年都会改变他们的规则。本文提出了一种新的球检测方法,以回应Kortes Robot Sepak Bola Indonesia(KRSBI)段的规则的改变为KRI 2017.对于人形划分,球在前一年竞争中的橙色网球变为白色,尺寸1 FIFA足球。对于轮式划分,将使用橙色大小4 FIFA足球。本文提出的算法基于轮廓和梯度霍夫圆形变换(GCHT),其能够检测任何颜色的球。基于轮廓主要用于检测球,如果机器人失败,GCHT将用于第二次机会。实验表明,该算法可以实现100 %(橙色球)的球检测精度,最多96℃(白色球)固定放置实验。在随机放置实验中,所提出的算法达到了93.3 %(橙色球)和96.6 %(白色球)的精度。此外,在实验中观察到的处理时间非常快,平均为37.76 fps。

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