车身零件无序自动抓取技术研究  

Research on Disorderly Auto Bin Picking Technology for Body Parts

作　　者：庄菁雄 ZHUANG Jingxiong(SAIC General Motors Corporation Limited,Shanghai 201206,China)

机构地区：[1]上汽通用汽车有限公司,上海201206

出　　处：《汽车实用技术》2024年第9期146-150,共5页Automobile Applied Technology

摘　　要：整车制造工厂车身车间零件样式和包装形式复杂多样,无序堆叠的小型金属零件自动抓取是实现车身车间上件完全自动化的关键环节。文章以一个无序堆叠包装的小型金属零件自动抓取为案例,搭建了包含机器人、抓手、料箱及视觉的验证系统,分别针对视觉抓取工艺中涉及的零件识别、路径规划、搬运定位三个关键步骤进行验证。研究结果发现,影响开动率和清箱率的三个关键因素是视觉传感器类型选择、抓取后零件定位精度、物料料箱设计形式及颜色。影响无序抓取的关键因素识别,确保了车身零件无序抓取系统性可靠性,为整车制造车身车间无序抓取应用起到借鉴作用。The styles and packaging forms of parts in the body shop of a vehicle manufacturing factory are complex and diverse,and the automatic picking of small metal parts that are stacked in an disorderly manner is a key link in achieving complete automation of parts loading.The article takes the automatic picking of a small metal part in an unordered stacked packaging as a case study and builds a verification system that includes robots,grippers,material boxes,and vision.The system focuses on three key steps involved in bin picking technology:part recognition,path planning,and transportation positioning.The research results show that the three key factors affecting the equipment running rate and bin cleaning rate are the selection of visual sensor type,the accuracy of part positioning after picking,and the design form and color of material bins.The identification of key factors affecting disorderly picking ensures the systematic reliability of disorderly picking of body parts,providing a reference for the application of disorderly bin picking in vehicle manufacturing workshops.

关 键 词：机器视觉 无序抓取 车身零件 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]