Application of minimum error entropy unscented Kalman filter in table tennis trajectory prediction.

Journal: PloS one
PMID: 36178888

Abstract

Table tennis is important and challenging project for robotics research, and table tennis robotics receives a lot of attention from academics. Trajectory tracking and prediction of table tennis is an important technology for table tennis robots, and its estimation accuracy is also disturbed by non-Gaussian noise. In this paper, a novel Kalman filter, called minimum error entropy unscented Kalman filter (MEEUKF), is employed to estimate the motion trajectory of physical model of a table tennis. The simulation results show that the MEEUKF algorithm shows outstanding performance in tracking and predicting the trajectory of table tennis compared to some existing algorithms.

Authors

  • Shenyue Luo
    Department of Sports, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, PR China.
  • Jianfeng Niu
    Sports Coaching College, Beijing Sport University, Beijing, PR China.
  • Peifeng Zheng
    Fujian Table Tennis, Badminton, and Tennis Management Center, Fujian Provincial Administration of Sport, Fuzhou, Fujian Province, PR China.
  • Zhihui Jing
    Department of Sports, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, PR China.

Keywords

External Resources

Popular Topics
Recent Journals