A successive learning neuro GA control system shooting an irregular moving object

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Abstract A successive learning control system based on a neural network technique with a genetic algorithm has been developed to simulate a human real-time learning process. As an application experiment, a 3-freedom arm robot shoots a ball equipped with a CCD camera at an irregular moving ring, where the success rate of shooting is improved by the successive learning control and the final value was 23% in average, 40% in maximum.

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