A novel method of shuttlecock trajectory tracking and prediction for a badminton robot

This paper proposes an aerodynamic analysis of the shuttlecock and a novel method for predicting shuttlecock trajectory. First, we have established a shuttlecock track data set by an infrared-based binocular vision system. Then the unscented Kalman filter algorithm is designed to further filter the...

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Bibliographic Details
Published inRobotica Vol. 40; no. 6; pp. 1682 - 1694
Main Authors Zhi, Junming, Luo, Deyuan, Li, Kui, Liu, Ya, Liu, Huaqiu
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.06.2022
Subjects
Algorithms
Binocular vision
Infrared tracking
Kalman filters
Neural networks
Prediction models
Radial basis function
Shuttlecocks
Vision systems
RBF network
Target tracking
Prediction
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Summary:This paper proposes an aerodynamic analysis of the shuttlecock and a novel method for predicting shuttlecock trajectory. First, we have established a shuttlecock track data set by an infrared-based binocular vision system. Then the unscented Kalman filter algorithm is designed to further filter the noise and visual recognition algorithm errors. Third, the radial basis function (RBF)-based track prediction model is designed. This method offers a concept to obtain the neural network model of different kinds of flying or moving objects. The experimental results show that the proposed method can predict the shuttlecock trajectory in real time at high accuracy and can be used for implementing the algorithm of return strategies in the near future.
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ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574721001053