计算机科学 ›› 2014, Vol. 41 ›› Issue (1): 83-87.

• 2013 CCF人工智能会议 • 上一篇    下一篇

无迹卡尔曼滤波在旋转乒乓球轨迹预测中的应用

张康洁,王奇志   

  1. 北京交通大学计算机与信息技术学院 北京100044;北京交通大学计算机与信息技术学院 北京100044
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61075035)资助

Application of Unscented Kalman Filter in Rotary Table Tennis Trajectory Prediction

ZHANG Kang-jie and WANG Qi-zhi   

  • Online:2018-11-14 Published:2018-11-14

摘要: 乒乓球机器人不能进行成功的智能回球的主要原因是对旋转球的轨迹预测不准确。减小轨迹预测误差可采取如下对策:分析旋转乒乓球飞行过程的运动学模型,采用无迹卡尔曼滤波(UKF)思想构建过程方程和观测方程,根据视觉系统观测得到的三维空间位置信息对乒乓球的三维空间位置、线速度及角速度进行在线估计。通过多次Matlab仿真对比实验和实际对比实验表明,UKF算法相对EKF算法在轨迹预测用时上可节省99%,跟踪误差更小。

关键词: 旋转乒乓球,轨迹预测,无迹卡尔曼滤波,乒乓球机器人

Abstract: The inaccurate results of ball trajectory prediction lead to ping-pong robot can not play the table tennis intelligently.In order to reduce the trajectory prediction error,the following measures may taken:The proposed method first analyses the kinematics model of the flying rotary ball,and then constructs the motion equation and observation equation of the ball’s flying trajectory based on the Unscented Kalman Filter (UKF).Finally ping-pong ball’s three-dimensional space position,velocity and angular velocity can be estimated,according to the three-dimensional space position information obtained by a visual observation system.The Matlab simulation experiments and real experimentals show that UKF algorithm compared to EKF algorithm in trajectory prediction time can be saved by 99%,and the tracking error is small.

Key words: Rotary table tennis,Trajectory prediction,Unscented kalman filter,Ping-pong robot

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