Vision-based robot path planning with deep learning

Abstract

In this paper, a new method based on deep convolutional neural network (CNN) for path planning of robot is proposed, the aim of which is to transform the mission of path planning into a task of environment classification. Firstly, the images of road are collected from cameras installed as required, and then the comprehensive features are abstracted directly from original images through the CNN. Finally, according to the results of classification, the moving direction of robots is exported. In this way, we build an end-to-end recognition system which maps from raw data to motion behavior of robot. Furthermore, experiment has been provided to demonstrate the performance of the proposed method on different roads.