摘要
针对智能制造生产线中的机器人抓取需求,设计了视觉伺服抓取系统;以视觉伺服控制系统为基础,设计并构建了视觉伺服数字孪生系统,实现了数字模型与物理模型的信息同步、互操作以及数字模型对物理模型状态的预测。对于目标物体的不同运动情况制定了3种目标运动状态预测方案,通过数字孪生系统对抓取实验的模拟结果确定使用不同方案的条件,为物理实体的抓取提供最优方案。以NAO机器人为实验平台实现了系统的抓取任务,通过实验验证了方案的有效性。
Aiming at the grasping demand of intelligent manufacturing line,the visual servo grabbing system was designed.Based on the visual servo control system,a visual servo Digital Twin(DT)system was designed.The information synchronization and interoperation between digital model and physical model and the prediction of the physical model state by digital model were realized.Three target motion state prediction schemes were developed for different motion conditions of the target object.The conditions of using different schemes were determined by the simulation results of grasping experiments with DT system.The NAO robot was used as the experimental platform to realize the system’s grasping task,and the effectiveness of the scheme was verified by experiments.
作者
吴迎年
杨弃
WU Yingnian;YANG Qi(School of Automation,Beijing Information Science&Technology University,Beijing 100192,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2019年第6期1528-1535,共8页
Computer Integrated Manufacturing Systems
基金
促进高校内涵发展“信息+”资助项目(5111823311)
北京信息科技大学重点研究培育资助项目(5221823307)
北京信息科技大学2019年教改重点资助项目(2019JGZD02)~~
