Abstract

Abstract This paper first studies the processing flow of image processing technology that preprocesses the image and adopts the method of polygonal approximation to identify the shape and localize the moving target. Then, the mobile platform of the warehouse logistics robot is designed. Then, the vision system of the robot was designed using image recognition technology to realize obstacle collision prediction and route planning. Finally, the robot’s localization and grasping abilities, trajectory following performance, and semantic segmentation abilities are analyzed using comparative experiments. The successful localization and grasping rates of the warehouse robots are all higher than 93%, and the trajectory following the straight line road section is better, with a maximum error of less than 21 mm. The mIoU of this paper’s method on the Cityscapes dataset is 78.85%, MPA is 86.05%, and PA is 96.89%, with good image segmentation performance. This study is of great significance for the development of the intelligent logistics field.

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