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

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-G...

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Bibliographic Details
Published in:PloS one 2022-09, Vol.17 (9), p.e0269257-e0269257
Main Authors: Luo, Shenyue, Niu, Jianfeng, Zheng, Peifeng, Jing, Zhihui
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Biology and Life Sciences
Engineering and Technology
Entropy
Estimation accuracy
Kalman filters
Noise
Normal distribution
Performance evaluation
Physical Sciences
Random noise
Research and Analysis Methods
Robotics
Simulation
Social Sciences
Table tennis
Tennis
Tracking
Trajectory analysis
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0269257