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Complementary data fusion in vision-guide and control of robotic tracking

Published online by Cambridge University Press:  17 January 2001

Y.M. Chen  and
C.S. Hsueh
Y.M. Chen
Affiliation:
Department of Electrical Engineering, Lee Ming Institute of Technology, Taipei 243, Taiwan (R.O.C.)ymchen@ccit.cc04.edu.tw
C.S. Hsueh
Affiliation:
Chung Shan Institute of Science & Technology(Taiwan)g881707@cc04.ccit.edu.tw
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Abstract

We present a data fusion control scheme for the hand-held camera of the SCORBOT-ER VII robot arm for learning visual tracking and interception. The control scheme consists of two modules: The first one generates candidate actions to drive the end-effector as accurate as possible directly above a moving target, so that the second module can handily take over to intercept it. The desired camera-joint coordinate mappings are generalized by Elman neural networks for a tracking module. The intercept module then determines a suitable intercept trajectory for the robot within the required conditions. The simulation results support the claim that it could be successfully applied to track and intercept a moving target.

Keywords

Data fusionVisual controlNeural network
Type
Research Article
Information
Robotica , Volume 19 , Issue 1 , January 2001 , pp. 53 - 58
Copyright
© 2001 Cambridge University Press

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