计算机与现代化 ›› 2009, Vol. 8 ›› Issue (8): 112-115.doi: 10.3969/j.issn.1006-2475.2009.08.031

• 计算机仿真 • 上一篇    下一篇

应用神经网络改善足球机器人传感系统

老建伟,张国良   

  1. 第二炮兵工程学院自动控制系,陕西 西安710025
  • 收稿日期:2008-08-14 修回日期:1900-01-01 出版日期:2009-08-21 发布日期:2009-08-21

Improvement of Soccer Robot Sensor System by Using Neutral Network

LAO Jian-wei,ZHANG Guo-liang   

  1. Department of Automatic Control, Second Institute of Artillery Engineering, Xi’an 710025, China
  • Received:2008-08-14 Revised:1900-01-01 Online:2009-08-21 Published:2009-08-21

摘要: 为了解决足球机器人单一传感器所提供的定位数据的精度及稳定性不足以满足控制系统要求的问题,本文利用BP神经网络算法的学习功能,将目标足球及机器人自身状态信息作为标定数据,将视觉、加速度计、电子罗盘等多个传感器信息作为网络输入,以神经网络输出辅助足球机器人对目标足球的捕捉。实验仿真结果表明,神经网络算法提高了对目标足球的定位以及机器人自定位的精度,起到了预期的效果。滤波平均相对误差优于传统的卡尔曼滤波。

关键词: 足球机器人, 传感器, 数据融合, 神经网络

Abstract: The accuracy and stability of position data, which is offered by the unique visual sensor, can not satisfy the requirement of control system. The learning function of the BP neutral network is used to solve this problem. The state information of football and robot is treated as sample data, the visual sensor, accelerometer and compass are treated as the input of network, and the outputs of the neutral network assist soccer robot to track football. Simulation shows that the neutral network improves the accuracy of the location for football and robot. The expected result is obtained. The average relative error is superior to the traditional Kalman filter.

Key words: football robot, sensor, data fusion, neutral network

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