DocumentCode :
551752
Title :
Neural-PID visual tracking of moving object
Author :
Cheng, Shen Shi
Author_Institution :
Jiangsu Teachers Univ. of Technol., Changzhou, China
Volume :
1
fYear :
2011
fDate :
29-31 July 2011
Abstract :
In this paper, an adaptive approach is presented to nonlinear system for real-time robotic visual tracking of a moving polyhedral object. A light stripe vision system consists of a laser-stripe sensor and a CCD the camera fixed to robot end-effector, and projects planar light on the polyhedral object. The geometric conditions can be provided to assure location of features of the polyhedral faces. The objective is to predict the location of features of the object on the image plane based on the light stripe vision system and then to determine an optimal control input that will move the camera so that the image features align with their desired positions. We first give the equations of observation and state-space by using the motion rules of the camera and the object. Then, the system can be represented as an MIMO ARMAX model and an efficient estimation model. The estimation model can process on-line estimation of the 3D related parameters between the camera and the object. Those parameters are used as on-line train values of neural network. The control scheme adopts a neural-PID controller that can adjust the PID controller parameters. The paper concludes with the simulation results and the computer simulation shows that the proposed method is effective to visual tracking of combining vision and control.
Keywords :
MIMO systems; autoregressive moving average processes; end effectors; image sensors; neurocontrollers; nonlinear control systems; object tracking; optimal control; robot vision; three-term control; MIMO ARMAX model; computer simulation; estimation model; laser-stripe sensor; light stripe vision system; moving polyhedral object neural-PID visual tracking; neural network; neural-PID controller; nonlinear system; optimal control; real-time robotic visual tracking; robot end-effector; Adaptation models; Lasers; Mathematical model; Optical imaging; Optical variables measurement; Position measurement; Robot vision systems; CCD; MIMO ARMAX; PID controller;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and Optoelectronics (ICEOE), 2011 International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-61284-275-2
Type :
conf
DOI :
10.1109/ICEOE.2011.6013141
Filename :
6013141
Link To Document :
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