Visual Measurement and Prediction of Ball Trajectory for Table Tennis Robot

Zhang, Zhengtao; Xu, De; Tan, Min

doi:10.1109/tim.2010.2047128

Cited by 103 publications

(62 citation statements)

References 10 publications

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“…How to get rid of the blurring noises caused by motion is a common problem in ping-pong ball detection algorithms. Like Modi, Zhang et al [22] used background subtraction to detect the motion of the ping-pong ball. However, instead of taking the motion as noise, they used the motion of the ball as a detection feature.…”

Section: Software Developmentmentioning

confidence: 99%

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Chen

Huang

Wan

et al. 2015

International Journal of Advanced Robotic Systems

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Developing a vision module for a humanoid ping-pong game is challenging due to the spin and the non-linear rebound of the ping-pong ball. In this paper, we present a robust predictive vision module to overcome these problems. The hardware of the vision module is composed of two stereo camera pairs with each pair detecting the 3D positions of the ball on one half of the ping-pong table. The software of the vision module divides the trajectory of the ball into four parts and uses the perceived trajectory in the first part to predict the other parts. In particular, the software of the vision module uses an aerodynamic model to predict the trajectories of the ball in the air and uses a novel non-linear rebound model to predict the change of the ball's motion during rebound. The average prediction error of our vision module at the ball returning point is less than 50 mm -a value small enough for standard sized ping-pong rackets. Its average processing speed is 120fps. The precision and efficiency of our vision module enables two humanoid robots to play ping-pong continuously for more than 200 rounds.

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Section: Software Developmentmentioning

confidence: 99%

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Chen

Huang

Wan

et al. 2015

International Journal of Advanced Robotic Systems

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“…As the vision systems of Ping-Pong robot need localize the positions of ball in real-time accurately, the popular vision systems [2][3] are almost adopting two or more than two cameras to construct a stereo camera system, localize the positions of the ball, and estimate the trajectories of the ball in real-time. Thus the synchronization of different cameras is important when the same motion is captured by different devices from different viewpoints which are used to localize the position of the ball accurately.…”

Section: Related Workmentioning

confidence: 99%

Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot

Xie

Liu

Xiong

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Temporal asynchrony between two cameras in the vision system is a usual problem in practice. In some vision task such as estimating fast moving targets, the estimation error caused by the tiny temporal asynchrony will become non-ignorable essentials. This paper will address on the asynchrony in the stereo vision system of humanoid Ping-Pong robot, and present a real-time accurate Ping-Pong ball trajectory estimation algorithm. In our approach, the complex Ping-Pong ball motion model is simplified by a polynomial parameter function of time t due to the limited observing time interval and the requirement of real-time computation. We then use the perspective projection camera model to re-project the ball's parameter function on time t into its image coordinates on both cameras. Based on the assumption that the time gap of two asynchronous cameras will maintain a const during very short time interval, we can obtain the time gap value and also the trajectory parameters of the Ping-Pong ball in a short time interval by minimizing the errors between the images of the ball in each camera and their re-projection images from the modeled parameter function on time t. Comprehensive experiments on real Ping-Pong robot cases are carried out, the results show our approach is more proper for the vision system of humanoid Ping-Pong robot, when concerning the accuracy and real-time performance simultaneously.

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“…part of hands or face of human player, are easily to be recognized as the orange ball. Zhang et al [8] constructed a stereovision system with a higher sample frequency of 100 fps. To detect the flying ball, it only adopted the adjacent frame difference of pixel gray value.…”

Section: Introductionmentioning

confidence: 99%

“…In order to determine the hitting position, a trajectory prediction is required after obtaining adequate measured ball positions. Zhang et al [8] utilized the iteration of dynamics model of the flying ball and collision model. However, the analysis of spinning ball was not involved.…”

Section: Introductionmentioning

confidence: 99%

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Ping-pong robotics with high-speed vision system

Wu²,

Lou

et al. 2012

2012 12th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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Abstract-The performance of vision-based control is usually limited by the low sampling rate of the visual feedback. We address Ping-Pong robotics as a widely studied example which requires high-speed vision for highly dynamic motion control. In order to detect a flying ball accurately and robustly, a multithreshold segmentation algorithm is applied in a stereo-vision running at 150Hz. Based on the estimated 3D ball positions, a novel two-phase trajectory prediction is exploited to determine the hitting position. Benefiting from the high-speed visual feedback, the hitting position and thus the motion planning of the manipulator are updated iteratively with decreasing error. Experiments are conducted on a 7 degrees of freedom humanoid robot arm. A successful Ping-Pong playing between the robot arm and human is achieved with a high successful rate of 88%.

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Visual Measurement and Prediction of Ball Trajectory for Table Tennis Robot

Cited by 103 publications

References 10 publications

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot

Ping-pong robotics with high-speed vision system

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Visual Measurement and Prediction of Ball Trajectory for Table Tennis Robot

Cited by 103 publications

References 10 publications

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Real-time accurate ball trajectory estimation with &#x201C;asynchronous&#x201D; stereo camera system for humanoid Ping-Pong robot

Ping-pong robotics with high-speed vision system

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Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot