A compensation method based on extreme learning machine to enhance absolute position accuracy for aviation drilling robot

2018 
To enhance the absolute position accuracy and solve complex modeling and computational complexity problems in traditional compensation methods for aviation drilling robots, a compensation method based on the extreme learning machine model was proposed in this article. The proposed method, in which the influence of geometric factors and the non-geometric factors of the robot is considered, builds a positional error prediction model based on extreme learning machine. As the input and output training data, the theoretical position and positional errors measured by a high-precision laser tracker were used to train and construct the extreme learning machine model. After the extreme learning machine model was constructed, the positional errors of prediction points could be predicted using the trained extreme learning machine. Then, the drilling robot controller could be directed to compensate for the predicted positional errors. To verify the correctness and effectiveness of the method, a series of experiments ...
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