Abstract:

To estimate the pose of industrial robot end effector quickly and accurately,a real-time estimation method was proposed based on UKF. This method was applied to industrial robot with laser feedback control system. In the industrial robot moving process, a rough estimation value of end effector pose was acquired by using forward position analysis and kinematics parameters of industrial robot in real time. And the position of a measured point fixed on end effector was obtained by a laser tracker. Then, UKF was employed to integrate the previous rough estimation value and the measured point position. The accurate pose of industrial robot end effector was evaluated by utilizing this method. Computer simulation results show that the presented method is achieved easily, and has fast calculation and high accuracy.

Key words: industrial robot, unscented Kalman filter(UKF), data fusion, laser tracker

摘要：

为了能在工业机器人运动过程中快速准确地估算出末端执行器的位姿,提出了一种基于unscented卡尔曼滤波器（UKF）的末端执行器位姿实时估算方法,并将该方法应用于以激光跟踪仪作为反馈系统的工业机器人中。首先,在工业机器人运动过程中实时获取各个关节运动参数，并结合工业机器人的结构参数计算末端执行器的位姿初值，然后借助于激光跟踪仪实时跟踪测量固定在机器人末端执行器上的一个测量点，运用UKF融合以上两类数据,估算出末端执行器的实时位姿。计算机仿真验证了该方法的有效性与实时性,同时表明该方法具有易于实现、计算速度快和精度高等优点。

关键词: 工业机器人, UKF, 数据融合, 激光跟踪仪