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基于焊件识别与位姿估计的焊接机器人视觉引导
引用本文:王斐,梁宸,韩晓光,茹常磊,李景宏.基于焊件识别与位姿估计的焊接机器人视觉引导[J].控制与决策,2020,35(8):1873-1878.
作者姓名:王斐  梁宸  韩晓光  茹常磊  李景宏
作者单位:东北大学机器人科学与工程学院,沈阳110169;东北大学信息科学与工程学院,沈阳110004
基金项目:中央高校基本科研业务费专项项目(N172608005,N182608003,N182612002);辽宁省科学事业公益研究基金项目(20170021);辽宁省自然科学基金项目(20180520007).
摘    要:为实现智能化柔性化焊接,并解决焊件本身立体结构遮挡焊缝影响视觉引导的问题,提出一种基于物体识别与位姿估计思想的焊接机器人视觉引导方法.首先,通过焊件的CAD模型离线建立焊接模型库;然后,在线计算焊件点云的VFH特征,与焊接模型库进行比对实现焊件识别,计算FPFH特征实现SAC-IA和ICP结合的两步位姿估计,并通过假设验证优化结果;最后,利用焊接模型库的焊接信息结合焊件位姿生成焊接轨迹,为焊接机器人提供视觉引导.实验结果表明,所提方法可以利用目标整体三维信息准确识别焊件并估计其姿态,进而引导机器人完成智能柔性的焊接操作.

关 键 词:焊接机器人  三维视觉引导  物体识别  位姿估计  假设验证  点云特征

Visual guidance of welding robot based on weldment recognition and pose estimation
WANG Fei,LIANG Chen,HAN Xiao-guang,RU Chang-lei,LI Jing-hong.Visual guidance of welding robot based on weldment recognition and pose estimation[J].Control and Decision,2020,35(8):1873-1878.
Authors:WANG Fei  LIANG Chen  HAN Xiao-guang  RU Chang-lei  LI Jing-hong
Affiliation:Faculty of Robot Science and Engineering,Northeastern University,Shenyang110169,China;College of Information Science and Engineering,Northeastern University,Shenyang110004,China
Abstract:A visual guidance method for the welding robot based on the weldment recognition and pose estimation is proposed to implement intelligent and flexible welding and solve the problem of that the visual guidance is affected by the three-dimensional structure of the weldment itself shielding the weld seam. Firstly, a welding model library is constructed by weldment CAD models off-line. Then, the viewpoint feature histogram(VFH) features of the weldment point cloud are calculated online and compared with the welding model library to implement weldment recognition. The fast point feature histogram(FPFH) features are calculated to implement a two-step pose estimation combining the sample consensus initial alignment(SAC-IA) and the ICP(iterative closest point) to obtain weldment pose. And the result is optimized by hypothesis verification. Finally, the welding trajectory is generated using the welding information in the welding model library combined with the pose of the weldment to provide visual guidance for the welding robot. The experimental results show that the method can accurately recognize the weldment and estimate its pose by using the target''s overall three-dimensional information, and guide the robot to implement intelligent and flexible welding operations.
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