Design and Implementation of Automatic Picking Robot Based on Deep Learning

The automatic picking robot, which utilizes advanced technologies such as physical scanning, online perception, and offline computing, has been applied in modern industries and logistics. This article focuses on the problem of automatic recognition and grasping in complex environments, focusing on the moving scene of picking up objects such as table tennis balls. Based on YOLOv5 object recognition, monocular ranging is applied to a gantry type sliding platform system. This automatic picking robot is deployed on the Windows system with YOLOv5, solving the problem of rapid recognition and distance measurement of target objects in complex scenes, and accurately picking up the recognized objects to the designated location. Through wireless communication module, accurately grasp the spatial position information of the mechanical claw. The experimental test results show that the automatic picking robot can accurately recognize the picking target, thus accurately picking up the target object to the designated position, providing certain reference value for the application research in the field of automatic picking robots.