Abstract
In this work, a deep learning-based approach was developed for the visual path perception of mobile robots, combined with computer vision technology. An experimental platform of differential wheeled mobile robots and a LabViewupper computing platform to realize the basic motion control and test the actual effect of the pre-trained DNN(Deep Neural Network) model was built. The training method of DNN, including the acquisition of data set, Deep Neural Network structure and training program was given out. Experimental results demonstrate the feasibility of applying deep learning to mobile robot's visual perception of path. It has a reference significance for improving the intelligent level of mobile robots.
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