数字孪生驱动的协作机器人状态监测方法研究  

Research on State Monitoring Method of Cooperative Robot Driven by Digital Twin

作　　者：赵墨波 Zhao Mobo(China Coal Research Institute,Beijing 100013,China;State Key Laboratory of Coal Mining and Clean Utilization,Beijing 100013,China;Beijing Mine Safety Engineering Technology Research Center,Beijing 100013,China)

机构地区：[1]煤炭科学技术研究院有限公司,北京100013 [2]煤炭资源高效开采与洁净利用国家重点实验室,北京100013 [3]北京市煤矿安全工程技术研究中心,北京100013

出　　处：《煤矿机械》2023年第8期210-212,共3页Coal Mine Machinery

基　　金：煤炭科学技术研究院技术创新基金Ⅰ类(2021CX-I-09)。

摘　　要：针对协作机器人的实时状态直接影响其在“人机共融”场景下的工作效率和安全性等问题,研究了基于数字孪生驱动的协作机器人状态监测方法。通过搭建数字孪生数据采集及存储系统实时采集状态数据,采用数据与模型的融合方法,将采集到的实时数据通过协作机器人数字模型进行可视化呈现,并采用“拖动示教”方式验证实体机器人的各轴转动。结果表明,该系统可以实时检测到机器人实体的状态,并保持一致运动。数据孪生驱动方法可以实现实时监测协作机器人的状态,保障人机协作过程中操作人员的安全性。Aiming at the problem that the real-time state of cooperative robot directly affects its work efficiency and security in the human-machine integration scenario,a state monitoring method of cooperative robot based on digital twin-driven was studied.The digital twin data acquisition and storage system was built for real-time collection of status data,and the fusion method of data and model was adopted to visualize the collected real-time data through the digital model of cooperative robot.The rotation of each axis of the solid robot was verified by dragging and teaching.The results show that the system can detect the state of robot entities in real time and keep consistent motion.The data twin-driven method can realize real-time monitoring of the state of cooperative robots,and ensure the safety of operators in the process of human-computer cooperation.

关 键 词：数字孪生 协作机器人 状态监测 可视化操作 拖动示教 

分 类 号：TD67[矿业工程—矿山机电]