为了解决大型压力容器铝合金罐体内部防浪板自动化焊接过程中,机器人系统对焊接点位检测不智能、检测精度不高、检测鲁棒性差的问题,设计了一种结构光视觉引导机器人的多特征融合三维焊接点位实时检测方法。首先对工件进行视觉特征提取,得出多个感兴趣区域(Region of interest,ROI),然后将多个特征融合,得到二维关键点,最后通过快速、无约束的系统标定确定三维预焊接点位。工业现场试验得出,相机坐标系下三维焊接点位提取最大误差为0.196 mm,平均误差0.099 mm,平均检测时间0.09 s,焊接点位检测精准、快速、智能,能够满足工业机器人焊接路径规划及自动焊接任务。
Abstract
In order to solve the problems of unintelligent detection of weld points
low detection accuracy and poor detection robustness of the robot system in the automated welding process of the internal anti-surge plate of aluminum alloy tanks of large pressure vessels
a multi-feature fusion 3D weld point real-time detection method for structural light visionguided robots is designed. First
the visual features are extracted from the workpiece to derive multiple regions of interest
then the multiple features are fused to obtain the 2D key points
and finally the 3D pre-weld points are determined by fast and unconstrained system calibration. Industrial field experiments show that the maximum error of 3D welding point extraction in camera coordinate system is 0.196 mm
the average error is 0.099 mm
and the average detection time is 0.09 s. The welding point detection is accurate
fast and intelligent
which can meet the industrial robot welding path planning and automatic welding tasks.