Affiliations: School of Computer Science and Engineering, Xi’an Technological University, Xi’an, China
Correspondence:
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Corresponding author. Quan Wang, School of Computer Science and Engineering, Xi’an Technological University, Xi’an, China. E-mail: seasurfer@sohu.com.
Abstract: In order to prove the practical application of intelligent AGV (Automated Guided Vehicle) in port, the special requirements of port AGV are analyzed, BP (Back Propagation) network algorithm is improved, AGV road sign recognition system and AGV visual system are established, and finally the recognition accuracy and response speed of visual system are tested through experiments. The results show that the characteristics of AGV can meet the complex port conditions, and prove that the improved algorithm has good practical application value, as well as good recognition rate and accuracy of the visual system height. This will be of positive significance to the future research on the application of port AGV system in China.
