基于嵌入式机器视觉的流水线分拣机器人设计
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引用本文:刘建文,沈瑞琳,马世登,林瑾.基于嵌入式机器视觉的流水线分拣机器人设计[J].计算技术与自动化,2024,(2):17-23
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作者单位
刘建文,沈瑞琳,马世登,林瑾 (广东东软学院广东 佛山 528000) 
中文摘要:针对传统流水线上人工错误率高、速度慢和人工成本高的问题,设计了一种深度学习的流水线智能分拣机器人来缓解流水线的压力。该机器人采用分层结构设计,上位机采用Jetson Nano来完成机器人的图像采集、识别和处理,下位机由STM32G0作为主控,通过舵机和电机实现机器人的功能控制。同时上位机与下位机之间进行有效的数据交互,实现了机器人的抓取和分拣协调工作。在实验测试中,该机器人能够通过学习样本实现自动分拣不同类型的对象,并且能够精确识别。该流水线分拣机器人融入了计算机视觉与嵌入式系统,不仅使分拣机器人结构更紧凑,而且有利于提高社会生产力水平,具有良好的应用前景。
中文关键词:流水线分拣机器人  深度学习  机器视觉  嵌入式系统
 
Design of an Assembly Line Sorting Robot Based on Embedded Vision
Abstract:In response to the problems of high manual error rate, slow speed and high labor cost on the traditional assembly line, a deep-learning assembly line intelligent sorting robot is designed to relieve the pressure on the assembly line. The robot is designed in a hierarchical structure, with the upper computer using Jetson Nano to complete the image acquisition, recognition and processing of the robot, and the lower computer using STM32G0 as the master control to realize the functional control of the robot through the servo and motor. At the same time, the upper computer and the lower computer interact with each other effectively to realize the robot’s grasping and sorting coordination work. In the experimental tests the robot was able to automatically sort different types of objects by learning samples with accurate and efficient recognition. This line sorting robot incorporates computer vision and embedded system, which not only makes the sorting robot more compact, but also helps to improve the productivity level of society and has great application prospects.
keywords:assembly line sorting robot  deep learning  machine vision  embedded systems
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