%0 Journal Article
%A HAN Song
%A HAN Xing
%A LIU Xiao-ping
%A WANG Gang
%T Robotic Sorting Method in Complex Scene Based on Deep Neural Network
%D 2019
%R 10.13190/j.jbupt.2019-015
%J Journal of Beijing University of Posts and Telecommunications
%P 22-28
%V 42
%N 5
%X A robotic sorting method based on deep neural network in complex scene is proposed to improve the sorting efficiency and recognition accuracy of parcels. The sorting method consists of three main parts. Firstly, the improved object detection algorithm is proposed. More detailed features are extracted by combining the multi-layer shallow layer with the final feature map to improve the speed and accuracy of recognition. Then, an optimal grab position detection network based on cascading convolution of key points is proposed to realize real-time estimation of the optimal sorting position of the parcel. Finally, by combining with the target capture optimal frame and the depth information of the scene, the robotic sorting operation can be completed by the target pose estimation algorithm based on the three-dimensional information, and the effectiveness of the method is verified by experiments.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-015