Liu Qiang, Ding Hairong
Shanghai Polytechnic University, Shanghai, China.
Front Neurorobot. 2022 May 11;16:820028. doi: 10.3389/fnbot.2022.820028. eCollection 2022.
The present work aims to accelerate sports development in China and promote technological innovation in the artificial intelligence (AI) field. After analyzing the application and development of AI, it is introduced into sports and applied to table tennis competitions and training. The principle of the trajectory prediction of the table tennis ball (TTB) based on AI is briefly introduced. It is found that the difficulty of predicting TTB trajectories lies in rotation measurement. Accordingly, the rotation and trajectory of TTB are predicted using some AI algorithms. Specifically, a TTB detection algorithm is designed based on the Feature Fusion Network (FFN). For feature exaction, the cross-layer connection network is used to strengthen the learning ability of convolutional neural networks (CNNs) and streamline network parameters to improve the network detection response. The experimental results demonstrate that the trained CNN can reach a detection accuracy of over 98%, with a detection response within 5.3 ms, meeting the requirements of the robot vision system of the table tennis robot. By comparison, the traditional Color Segmentation Algorithm has advantages in detection response, with unsatisfactory detection accuracy, especially against TTB's color changes. Thus, the algorithm reported here can immediately hit the ball with high accuracy. The research content provides a reference for applying AI to TTB trajectory and rotation prediction and has significant value in popularizing table tennis.
本工作旨在加速中国体育发展，推动人工智能（AI）领域的技术创新。在分析了AI的应用与发展之后，将其引入体育领域并应用于乒乓球比赛和训练中。简要介绍了基于AI的乒乓球轨迹预测原理。发现预测乒乓球轨迹的难点在于旋转测量。因此，利用一些AI算法对乒乓球的旋转和轨迹进行预测。具体而言，基于特征融合网络（FFN）设计了一种乒乓球检测算法。在特征提取方面，采用跨层连接网络增强卷积神经网络（CNN）的学习能力，简化网络参数以提高网络检测响应。实验结果表明，训练后的CNN检测准确率可达98%以上，检测响应在5.3毫秒以内，满足乒乓球机器人视觉系统的要求。相比之下，传统的颜色分割算法在检测响应方面具有优势，但检测准确率不理想，尤其是针对乒乓球颜色变化时。因此，本文报道的算法能够以高精度立即击球。该研究内容为将AI应用于乒乓球轨迹和旋转预测提供了参考，对乒乓球的普及具有重要价值。
