A tracking and predicting scheme for ping pong robot

We describe a new tracking and predicting scheme applied to a lab-made ping pong robot. The robot has a monocular vision system comprised of a camera and a light. We propose an optimized strategy to calibrate the light center using the least square method. An ellipse fitting method is used to precis...

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Bibliographic Details
Published in:Journal of Zhejiang University. C Science 2011-02, Vol.12 (2), p.110-115
Main Authors: Zhang, Yuan-hui, Wei, Wei, Yu, Dan, Zhong, Cong-wei
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Communications Engineering
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Electrical Engineering
Electronics and Microelectronics
Fittings
Instrumentation
Mathematical models
Networks
Neural networks
Robots
Tracking
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Summary:We describe a new tracking and predicting scheme applied to a lab-made ping pong robot. The robot has a monocular vision system comprised of a camera and a light. We propose an optimized strategy to calibrate the light center using the least square method. An ellipse fitting method is used to precisely locate the center of ball and shadow on the captured image~ After the triangulation of the ball position in the world coordinates, a tracking algorithm based on a Kalman filter outputs an accurate estimation of the flight states including the ball position and velocity. Furthermore, a neural network model is constructed and trained to predict the following flight path. Experimental results show that this scheme can achieve a good predicting precision and success rate of striking an incoming ball. The robot can achieve a success rate of about 80% to return a flight ball of 5 rn/s to the opposite court.
ISSN:1869-1951
1869-196X
DOI:10.1631/jzus.C0910528