Abstract
A trajectory prediction method based on kalman filter algorithm (KF) and support vector machine algorithm (SVM) is proposed to predict the trajectory prediction of fast flight ping-pong in the research of ping-pong robot. This method combines the real-time performance of KF and the stability of SVM. By comparing the correlation coefficient between the predicted value and the measured value, the method intelligently selects an appropriate algorithm for the trajectory prediction of ping-pong. Finally, the result of simulation experiment of fast flight ping-pong shows that the method has good stability to the trajectory prediction of ping-pong, and the prediction accuracy is obviously improved compared with the single algorithm.
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Acknowledgements
This paper was partially supported by the National Natural Science Foundation (61374040, 61503205).
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Cheng, Q., Wang, C. (2018). A Method of Trajectory Prediction Based on Kalman Filtering Algorithm and Support Vector Machine Algorithm. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2017 Chinese Intelligent Systems Conference. CISC 2017. Lecture Notes in Electrical Engineering, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-6496-8_46
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DOI: https://doi.org/10.1007/978-981-10-6496-8_46
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