PEMANFAATAN METODE WAVELET PADA ROBOT SEPAKBOLA BERBASIS MACHINE LEARNING GOOGLE TENSORFLOW

Aryanto Aryanto, Melvi Melvi
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Abstract

Humanoid Football robot that will be investigated is a wheeled model developed with the ability to predict or prediction in a football field with high accuracy and image resolution. This robot is expected to be able to keep the goal for up to 25 minutes with a cruising reach of 100 m. Also, the robot can monitor or monitor the desired area so that it can keep the goal from attacks from the opposing robot. This robot is expected to complete prediction missions towards the ball and autonomous monitoring without being controlled by the pilot. Robot control is carried out by a Ground Control Station (GCS) computer. The goalkeeper's robot process uses Google TensorFlow's machine learning technology that is integrated with the wavelet method to enable this robot to keep the goalposts from the area effectively and efficiently. Keywords: robot, machine learning, prediction, Ground Control Station, wavelet method
基于googletensorflow机器学习的小波机器人sepakbola方法
将被研究的人形足球机器人是一种轮式模型,具有在足球场上进行预测或预测的能力,具有高精度和图像分辨率。该机器人预计能够保持目标长达25分钟,巡航距离为100米。此外,机器人还可以监视或监视期望的区域,以防止对方机器人攻击目标。该机器人有望在不受驾驶员控制的情况下完成对球的预测和自主监测任务。机器人控制由地面控制站(GCS)计算机执行。守门员的机器人过程使用了谷歌TensorFlow的机器学习技术,该技术与小波方法相结合,使机器人能够有效地保持门柱远离该区域。关键词:机器人,机器学习,预测,地面控制站,小波方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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