A tracking and predicting scheme for ping pong robot

Autor:	Yuan-hui Zhang, Dan Yu, Wei Wei, Congwei Zhong
Rok vydání:	2011
Předmět:	Artificial neural network Computer science business.industry General Engineering Kalman filter Ellipse Calibration Ball (bearing) Ping pong Robot Computer vision Artificial intelligence business Monocular vision Simulation
Zdroj:	Journal of Zhejiang University SCIENCE C. 12:110-115
ISSN:	1869-196X 1869-1951
DOI:	10.1631/jzus.c0910528
Popis:	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 m/s to the opposite court.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::128bec84ee3fe8a79d1352e3b99b3dc8 https://doi.org/10.1631/jzus.c0910528 Zobrazit plný text záznamu