Robot route planning method by employing improved convolutional neural network based on K mean value
A convolutional neural network and path planning technology, which is applied in the field of robot path planning based on K-means improved convolutional neural network, can solve the problems of large number of convolutional neural network parameters, gradient dispersion, and parameters that cannot be learned to optimal values. , to achieve fast training speed, improve accuracy, and solve the effect of gradient dispersion problem
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 The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of this application.
 The invention provides a robot path planning method based on K-means improved convolutional neural network, which adopts weight sharing and local connection to reduce the number of parameters to be learned and improve efficiency.
 Such as figure 1 As shown, each layer and the previous layer are locally connected instead of fully connected. The nerve cells of the first layer are connected to the three nerve cells of the 1-1 laye...
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