Application and research of trajectory prediction of table tennis robot based on LSTM

Quanyu Song; Rong Lu

doi:10.1117/12.3035167

19 July 2024 Application and research of trajectory prediction of table tennis robot based on LSTM

Quanyu Song, Rong Lu

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132132D (2024) https://doi.org/10.1117/12.3035167
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

With the development of science and technology, table tennis robots are becoming more and more common in the daily competition and training of athletes. This study is mainly for the research and development of the vision of table tennis robots. This study uses long and short time memory network (LSTM) to predict table tennis trajectory. We collected a large amount of table tennis sport data and used it to train and test our LSTM model. By analyzing the motion trajectory of the ball, we designed an effective LSTM architecture that can capture the complex dynamic properties of table tennis movements. Experimental results show that our model achieves remarkable success in table tennis trajectory prediction, with higher accuracy and robustness compared to traditional methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Quanyu Song and Rong Lu "Application and research of trajectory prediction of table tennis robot based on LSTM", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132132D (19 July 2024); https://doi.org/10.1117/12.3035167

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