5G+AI：生产过程中物品的智能分拣
技术
- 分析与建模 - 计算机视觉软件
适用行业
- 设备与机械
- 运输
适用功能
- 离散制造
- 物流运输
用例
- 计算机视觉
服务
- 软件设计与工程服务
挑战
在工业制造和物流等许多行业中，对产品或物体的识别、检测和分类有很多需求。传统的基于人工视觉的检测方法容易出现疲劳，无法始终保证较高的检测效率，而且由于人眼本身的生理限制，在速度和准确率方面难以达到高标准。因此，传统的人工检测方式制约了生产力水平的发展和提高，已难以满足生产需要。越来越多的基于机器视觉的分拣机器人被广泛应用于各种工业生产线。即通过工业相机获取目标图像信息，完成抓取目标的排序。传统工业机器人视觉分拣系统采用经典的计算机视觉理论，如不变量距离、模板匹配、SURF特征等算法来识别和定位工件，对场景环境、工件形状和背景颜色有更高的要求。现场输送带上的工件和物体可能形状复杂，姿态各异，密密麻麻地放置在一起。在这种情况下，经典的视觉识别和定位算法无法满足高识别率和高精度的要求。
解决方案
在基于5G+AI的机器视觉分拣系统解决方案中，集成5G终端的工业相机解决了频繁更换网线的痛点，部署方式更加灵活。将图像发送回云端，以使用深度学习 AI 来检测图像解决方案。
运营影响
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