东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2017, Vol. 38 ›› Issue (1): 27-31.DOI: 10.12068/j.issn.1005-3026.2017.01.006

• 信息与控制 • 上一篇    下一篇

一种新的羽毛球拍挥拍轨迹识别方法

崔婀娜1,2，陈星池1，赵海1，李晗1   

  1. (1.东北大学 计算机科学与工程学院，辽宁 沈阳110169; 2.沈阳大学 信息工程学院，辽宁 沈阳110044)
  • 收稿日期:2015-08-26 修回日期:2015-08-26 出版日期:2017-01-15 发布日期:2017-01-13
  • 通讯作者: 崔婀娜
  • 作者简介:崔婀娜(1979-)，女，辽宁沈阳人，东北大学博士研究生; 赵海(1959-)，男，辽宁沈阳人，东北大学教授，博士生导师.
  • 基金资助:
    国家科技支撑计划项目(2012BAH82F00); 辽宁省科学技术计划项目(2015401039); 沈阳市科技专项(F15-199-1-03).

A Novel Swing Trajectory Recognition Method for Badminton Racket

CUI E-nuo1,2，CHEN Xing-chi1， ZHAO Hai1， LI Han1   

  1. 1.School of Computer Science & Engineering， Northeastern University， Shenyang 110169， China; 2.School of Information Engineering， Shenyang University， Shenyang 110044， China.
  • Received:2015-08-26 Revised:2015-08-26 Online:2017-01-15 Published:2017-01-13
  • Contact: CHEN Xing-chi
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摘要： 为了更加精确地识别羽毛球拍的运动轨迹，提出一种多传感器融合的挥拍轨迹识别方法(TRM，trajectory recognition method).使用放置在球拍拍柄底部的智能设备进行数据采集，该设备由加速度计、陀螺仪和磁力计的多传感器组成.首先，使用加速度计和磁力计对陀螺仪进行修正，改进基于卡尔曼滤波器的四元数姿态解算精度并得到姿态角.其次，使用旋转矩阵去除加速度的重力分量，再对加速度数据进行频域数值积分得到速度和位移，采用最小二乘拟合多项式剔除数值积分过程中产生的累积误差.最后，结合姿态角、速度和位移，识别出挥拍轨迹.实验结果表明，提出的TRM具有良好的有效性.与传统时域积分轨迹识别方法相比，TRM的挥拍轨迹识别率更高.TRM可以更准确地进行羽毛球拍运动轨迹识别.

关键词: 羽毛球拍, 智能设备, 多传感器, 姿态解算, 挥拍轨迹识别

Abstract: A novel trajectory recognition method (TRM) using multi-sensor fusion was proposed to extract the motion trajectory of badminton racket more accurately. The smart device was placed in the bottom of the handle of the racket， which was composed of accelerometer， magnetometer and gyroscope. Firstly， the date of gyroscope was optimized by accelerometer and magnetometer. By combining gyroscope error， the attitude angle of trajectory could be obtained using TRM. Then the speed and the displacement were calculated by frequency domain integral of acceleration data. The accumulated error of frequency domain integral is removed by the least squares fitting method.Finally， the trajectory was identified by attitude angle， the speed and the displacement. Multiple experimental results show that the validity of TRM is great. Compared with the traditional time domain integral trajectory recognition method， the identification accuracy of TRM is higher. TRM can recognize the trajectory of badminton racket more accurately.

Key words: badminton racket, smart device, multi-sensor, attitude algorithm, swing trajectory recognition

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