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Published on: June 16, 2021
Application of minimum error entropy unscented Kalman filter in table tennis trajectory prediction
Shenyue Luo1, Jianfeng Niu2, Peifeng Zheng3
1Department of Sports, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, PR China.
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.
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