제어로봇시스템학회:학술대회논문집
- 1996.10b
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- Pages.302-305
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- 1996
Visual servoing of robot manipulators using the neural network with optimal structure
최적화된 신경회로망을 이용한 동적물체의 비주얼 서보잉
Abstract
This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.
Keywords
- visual servoing;
- a optimal structure;
- a predictive control;
- a evolutionary programming;
- a evolution strategies