Rebound Modeling of Spinning Ping-Pong Ball Based on Multiple Visual Measurements
Rebound Modeling of Spinning Ping-Pong Ball Based on Multiple Visual Measurements
复制标题
基于多重视觉测量的旋转乒乓球的反弹建模
DOI：
10.1109/tim.2016.2555179
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发表时间：
2016-05
影响因子：
5.6
通讯作者：
Zhang Yifeng
中科院分区：
文献类型：
--
作者：
Zhao Yongsheng;Xiong Rong;Zhang Yifeng
旋转球与桌面碰撞问题是旋转飞行物体运动轨迹分析中的一个普遍问题，其研究既重要又复杂。传统的研究要么将碰撞过程简化为一个黑箱，即碰撞前后球的运动状态发生突变，要么假设恢复系数和摩擦系数在整个碰撞过程中是简单的分段线性甚至常数。本文首先分析了碰撞动力学的机理，通过数学推导得出乒乓球与球台的碰撞是一个连续的过渡过程，其碰撞持续时间是一个与球的运动状态无关的常数。这两个结论也验证了视觉测量使用超高速相机。然后，我们提出了一个新的反弹模型的中值定理，动量定理，角动量定理。该模型的新奇在于，它的力和参数被制定为连续的函数有关的球的运动状态，这是更准确的，而不是常数。这些函数随时间的积分可以通过使用中值定理来制定，并且它们的表达式使用具有由位置视觉系统和云台视觉系统收集的大数据集的多层感知来学习。实验结果验证了该模型的有效性和准确性。
The research on the collision between a spinning ball and a table, as a general issue for the trajectory analysis of the spinning-flying objects, is important but complicated. Traditionally, it is studied either by simplifying the collision process as a black box in which the ball's motion state changes abruptly before and after collision, or by assuming that the coefficient of restitution and the coefficient of friction are simply piecewise linear or even constant during the whole collision process. In this paper, we first analyze the mechanism of the collision dynamics and conclude from mathematical derivations that the collision between a ping-pong ball and a table is a continuous transition process and its collision duration is a constant irrelevant to the ball's motion state. These two conclusions are also verified by the visual measurement using an ultrahigh-speed camera. Then, we propose a novel rebound model using the mean value theorem, momentum theorem, and angular momentum theorem. The novelty of the proposed model is that the forces and the parameters in it are formulated as the continuous functions related to the ball's motion state, which is more accurate, rather than as constants. The integrations of these functions over time can be formulated by using the mean value theorem, and their expressions are learned using multilayer perception with a large data set collected by the position vision system and the pan-tilt vision system. The experimental results verify the effectiveness and accuracy of the proposed model.
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DOI：
10.1109/icra.2014.6907456
发表时间：
2014-09
期刊：
2014 IEEE International Conference on Robotics and Automation (ICRA)
影响因子：
--
作者：
Yifeng Zhang;Yongsheng Zhao;R. Xiong;Yue Wang;J. Wang;Jian Chu
通讯作者：
Yifeng Zhang;Yongsheng Zhao;R. Xiong;Yue Wang;J. Wang;Jian Chu
影响因子：
0.9
作者：
Cross, R
通讯作者：
Cross, R
影响因子：
0.9
作者：
G. Barnes
通讯作者：
G. Barnes
使用期望最大化算法的基于模型的乒乓机器人旋转球的运动状态估计和轨迹预测
影响因子：
3.3
作者：
Zhao, Yongsheng;Xiong, Rong;Zhang, Yifeng
通讯作者：
Zhang, Yifeng
DOI：
10.1109/robio.2011.6181649
发表时间：
2011-12
期刊：
2011 IEEE International Conference on Robotics and Biomimetics
影响因子：
--
作者：
A. Nakashima;Yuki Ogawa;Chunfang Liu;Y. Hayakawa
通讯作者：
A. Nakashima;Yuki Ogawa;Chunfang Liu;Y. Hayakawa