Research on Inspection and Diagnosis Robots for Plant Facilities-Trajectory Tracking Control by Fuzzy Genetic Algorithm and Self-Positioning Correction Method by Deep Learning

This paper proposes an autonomous trajectory tracking control method for automatic intelligent inspection and diagnosis robots (IIDR) in various factories. Firstly, the basic concept of IIDR system is described. Fuzzy trajectory tracking control rules for automatic walking along the inspection path when IIDR automatic inspection equipment is built. And a method to explore the best fuzzy control rules based on multi-objective genetic algorithm (MOGA) is proposed. In order to solve the positioning error of IIDR during automatic walking, an automatic position correction method based on deep learning Convolutional Neural Network (CNN) is proposed. The result of the method is very accurate. Finally, the effectiveness of the various methods proposed in this paper is verified by using typical vehicle experiments.