基于深度学习的高速机器人分拣系统机器视觉技术研究

Shengqiang Bao
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摘要

随着工业自动化水平的提高和科学技术的进步,机器人的数量越来越多,应用场景越来越复杂,对机器人的自动化、智能、精密、稳定性和灵活性的要求也越来越高。机器视觉是指用机器代替人眼进行测量和判断。机器视觉的最终目标是使机器能够像人眼一样准确地观察和理解输入的图像数据,并最终做出决策,以达到自主适应环境的目的。在传统的工业生产线上,工件分拣的任务是手工进行的,不仅效率低,而且成本高。将机器视觉技术应用于工业机器人的分拣任务是工业自动化的发展趋势。本文根据中国生产行业的实际需求,基于深度学习算法、机器视觉等先进技术,构建了产品生产的高速机器人分拣系统,以提高机器人分拣系统的整体运行效果。
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Research on Machine Vision Technology of High Speed Robot Sorting System Based on Deep Learning
With the improvement of industrial automation level and the progress of science and technology, the number of robots is increasing, the application scenarios are becoming more and more complex, and the requirements for automation, intelligence, precision, stability and flexibility of robots are also increasing. Machine vision refers to the use of machines instead of human eyes for measurement and judgment. The ultimate goal of machine vision is to enable machines to observe and understand the input image data accurately like human eyes, and finally make decisions to achieve the purpose of adapting to the environment autonomously. In the traditional industrial production line, the task of sorting workpieces is carried out manually, which is not only inefficient but also costly. It is the trend of industrial automation to apply machine vision technology to sorting tasks of industrial robots. According to the actual needs of China's production industry, based on advanced technologies such as deep learning algorithm and machine vision, this paper constructs a high-speed robot sorting system for product production to improve the overall operation effect of the robot sorting system.
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