Application of Kalman Filter in Track Prediction of Shuttlecock

摘要：

This paper deals with the application of Kalman filter for optimizing and filtering the position signal of shuttlecock obtained by the vision servo system of Shuttlecock Robot 1. Non-uniform mass distribution and air resistance effect can make much noise not only in vision recognition but also in kinematic model analysis of shuttlecock. The Kalman filter algorithm is used to filter the shuttlecock position signal by taking the error of measurement and the error of shuttlecock motion model into account. Besides, by considering the requirement of fast moving control, we reduce dimensions of state vector by decomposition of shuttlecock motion to shorten the executive cycle. The simulation results show its affectivity on improving the accuracy of track prediction. It can also accomplish track prediction fast and accurately when applied on ‘Shuttlecock Robot.

关键词： least squares Kalman filter air resistance Shuttlecock Robot

作者: Man Yongkui Zhao Liang Hu Jingxin

作者单位: School of Information Science and Engineering,Northeastern University,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 2205-2210

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）