为了提高选择顺应性装配机器手臂(SCARA)机器人平面定位的精度, 采用网格模型结合最小距离误差逼近的方法, 首先构建SCARA机器人平面定位的简化模型, 概述网格模型构建原理, 然后通过视觉采集机器人末端第1次到达的实际点与期望点相对位置关系, 构建可变参量的起始网格模型, 再采用最小距离误差逼近, 求解下一步构建可变参量网格模型起始点, 最后由期望点在网格模型中位置分布情况决定模型粒度点的收敛更新方向。结果表明, 视觉引导的定位补偿策略弥补了因模型不精准而造成的平面定位精度不高的现象; 空间插值补偿法定位精度为1mm~3mm, 平面定位补偿精度较之有较大提高。该方法调节的参量单一、机器末端移动次数明确、工业应用性强。

In order to improve the plane positioning accuracy of selective compliance assembly robot arm (SCARA) robot, the method combined compensation strategy based on grid model and the minimum error approximation principle was proposed. Firstly, a simplified model for SCARA robot was established and grid model principle was summarized. Secondly, an initial grid model was constructed by analyzing the location relationship between the first-time reached actual point and the desired point. The starting point of the variable parameter grid model in the next step was constructed by using the minimum distance error approximation method. Finally, the convergence and update direction were determined by the location of the desired point in grid model. The results show that the positioning compensation strategy of visual guidance makes up the phenomenon that the plane positioning accuracy is not high because of the inaccuracy of the model. The accuracy of the positioning compensation strategy is much better than 1mm~3mm of the spatial interpolation compensation method. The proposed method has brief parameter regulation, clearly mobile times and strong industrial application.