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A position estimation scheme in visual servo system with single camera mounted on a robot is proposed. The scheme combines the techniques of depth-from-motion and depth-from-defocus to satisfy the real-time requirement. For long distance moving objects, the position estimation of the object is obtained by Plucker expression in Grassmann-Cayley algebra. For close distance moving object, a multilayer feedforward neural network is employed to recover the object position from defocused image. A criterion is used to switch between these two methods. The improvements of estimation accuracy by using the proposed method are verified by experimental results.
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on (Volume:6 )
Date of Conference: 15-19 June 2004