基于IGCF算法和CSF-PPSO-ESN算法的工业机器人末端执行器位姿重复性检测

Industrial robot end effector pose repeatability test based on IGCF and CSF-PPSO-ESN algorithm

工业机器人在智能制造领域具有举足轻重的地位,其末端执行器位姿的重复性是衡量机器人完成精密作业能力的重要指标。本文针对机器人末端执行器的位姿重复性在线检测,提出了基于方向余弦的位姿重复性测量的理论模型。设计了一种基于改进的高斯曲线拟合(IGCF)算法和三次样条拟合-多目标粒子群-回声状态网络(CSF-PPSO-ESN)算法的位姿偏差检测方法。通过获取十字激光图像偏角和中心点位置,实现了机器人末端执行器位姿偏差的测量。实验表明,测量系统的位移测量精度为±1.5μm,角度测量精度为±2 arc-sec。本文所述的位姿重复性检测方法,为工业机器人末端执行器位姿稳定性的在线实时监测提供了参考。

Industrial robots play an essential role in intelligent manufacturing.The repeatability of the end effector is an important indicator to measure the robot′s ability to complete precision operation.In this article,a theoretical model of the robot end effector′s pose repeatability accuracy measurement is proposed,which is based on directional cosine.A pose deviation detection method is designed,which is based on the improved Gaussian curve fitting(IGCF)algorithm and cubic spline fitting-Pareto particle swarm optimization-echo state network(CSF-PPSO-ESN)algorithm.The measurement of the robot end effector′s pose repeatability accuracy is realized by acquiring the cross-laser pattern′s offset angle and center point position.The experimental results show that the position measurement error after compensation is ±1.5μm,and the angle measurement error after compensation is ±2 arc-sec.The proposed pose deviation detection method provides a reference for the online real-time measuring of the robot end effector′s pose repeatability accuracy.